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Ansible Trainers Guide for DevOps Engineers—Bangalore

Introduction: Problem, Context & Outcome
Bangalore-based technology teams operate inside fast-paced DevOps environments where automation decides delivery speed and system stability. However, many engineers still struggle with inconsistent configurations, manual provisioning, and fragile deployment processes. As infrastructure spreads across cloud platforms and hybrid setups, small automation gaps quickly turn into large operational issues. Meanwhile, organizations expect engineers to deploy faster, recover quicker, and maintain predictable environments. Because expectations rise continuously, surface-level Ansible knowledge no longer meets enterprise demands.
Therefore, Ansible Trainers In Bangalore help professionals bridge the gap between knowing Ansible and using it confidently in production. With expert guidance, learners develop hands-on automation skills aligned with real DevOps workflows. As a result, engineers gain job-ready expertise, confidence, and career growth opportunities within Bangalore’s competitive tech ecosystem.
Why this matters: Practical local training accelerates automation success and professional growth.
What Is Ansible Trainers In Bangalore?
Ansible Trainers In Bangalore refers to experienced automation experts who provide hands-on Ansible training tailored to industry needs. Instead of focusing only on commands, trainers emphasize automation design, structure, and real-world usability. Because Bangalore hosts startups, enterprises, and global delivery centers, training reflects actual DevOps challenges faced daily.
Developers and DevOps engineers learn how to automate provisioning, configuration management, and application deployment using Ansible. Trainers guide learners through practical scenarios involving cloud environments, CI/CD pipelines, and version control systems. Moreover, learners receive mentorship on industry best practices that scale beyond small environments.
As a result, professionals convert theoretical knowledge into production-grade automation skills.
Why this matters: Practical mentoring ensures Ansible skills translate directly into workplace impact.
Why Ansible Trainers In Bangalore Is Important in Modern DevOps & Software Delivery
Modern DevOps teams in Bangalore release software at a rapid pace. Because delivery cycles shorten, manual configurations introduce delays and risk. Ansible Trainers In Bangalore help teams replace repetitive tasks with reliable automation that supports continuous delivery.
Additionally, Ansible integrates smoothly with CI/CD pipelines, cloud infrastructure, and Agile workflows. Trainers explain how automation fits into real delivery pipelines and environment standardization processes. Consequently, teams achieve faster releases with fewer failures.
As Bangalore strengthens its position as a global engineering hub, companies increasingly seek automation-ready DevOps professionals.
Why this matters: Skilled automation directly supports speed, stability, and scalability.
Core Concepts & Key Components
Playbook Design and Structure
Purpose: Define automation logic clearly and consistently.
How it works: Playbooks describe desired system states using structured YAML.
Where it is used: Application deployment and configuration management.
Role-Based Automation
Purpose: Enable modular and reusable automation.
How it works: Roles organize tasks, templates, variables, and handlers logically.
Where it is used: Large-scale infrastructure automation.
Inventory Management
Purpose: Manage environments efficiently.
How it works: Inventories define hosts and groups dynamically.
Where it is used: Cloud, hybrid, and multi-region setups.
Variables and Templates
Purpose: Customize automation for different environments.
How it works: Jinja templates and variables control behavior dynamically.
Where it is used: Multi-environment deployments.
Error Handling and Execution Control
Purpose: Maintain automation stability.
How it works: Conditions and handlers control execution flow.
Where it is used: Production automation pipelines.
CI/CD and Tool Integration
Purpose: Enable continuous automation.
How it works: Ansible integrates with pipelines and DevOps tools.
Where it is used: End-to-end delivery workflows.
Why this matters: Core components ensure automation remains scalable, safe, and predictable.
How Ansible Trainers In Bangalore Works (Step-by-Step Workflow)
First, trainers evaluate learners’ automation experience and identify gaps. Next, learners build foundational automation skills using real-world infrastructure examples. Then, trainers guide learners through structured playbooks, role creation, and inventory optimization.
Afterward, automation integrates with CI/CD pipelines commonly used in Bangalore-based organizations. Learners practice execution control, rollback strategies, and environment consistency. Finally, learners apply automation patterns to production-style systems.
Throughout the workflow, training mirrors real DevOps lifecycle stages rather than isolated exercises.
Why this matters: Step-by-step instruction builds confidence for real production work.
Real-World Use Cases & Scenarios
Technology companies in Bangalore rely on Ansible to standardize infrastructure across multiple environments. DevOps teams automate application deployments during frequent releases. Developers benefit from consistent development and testing setups.
QA teams validate configuration accuracy during release cycles. SRE teams automate remediation workflows to improve uptime. Businesses gain faster delivery, reduced incidents, and improved operational efficiency.
Why this matters: Real-world automation delivers measurable business value.
Benefits of Using Ansible Trainers In Bangalore
Productivity: Faster automation through guided, hands-on learning Reliability: Consistent configurations across environments Scalability: Automation that grows with infrastructure Collaboration: Shared automation standards across teams Why this matters: Professional training multiplies automation effectiveness and confidence.
Challenges, Risks & Common Mistakes
Many learners focus too much on syntax and ignore automation design. Others create oversized playbooks that fail to scale. Additionally, weak inventory design complicates long-term maintenance.
Ansible Trainers In Bangalore address these issues by teaching structured patterns, real-world design strategies, and troubleshooting approaches. Learners understand how to avoid common pitfalls and build resilient automation.
Why this matters: Avoiding mistakes reduces downtime and long-term technical debt.
Comparison Table
Manual OperationsAnsible AutomationManual provisioningAutomated provisioningError-prone stepsPredictable executionSlow releasesFaster deploymentsHardcoded scriptsReusable playbooksLimited scaleHigh scalabilityConfiguration driftStandardized environmentsReactive fixesProactive automationHigh operational costOptimized efficiencyLow reuseRole-based reuseLow reliabilityHigh reliability Why this matters: Comparison clearly highlights automation advantages.
Best Practices & Expert Recommendations
Design automation using reusable roles and clean inventories. Additionally, test automation thoroughly in staging environments. Secure sensitive data carefully and document automation clearly for team usage.
Furthermore, integrate Ansible workflows with CI/CD pipelines and review execution results regularly.
Why this matters: Best practices ensure automation sustainability and long-term success.
Who Should Learn or Use Ansible Trainers In Bangalore?
Developers benefit from automated environment provisioning and consistency. DevOps engineers gain enterprise-grade automation expertise. Cloud engineers, SREs, and QA professionals improve system reliability and delivery confidence.
Beginners build strong automation foundations, while experienced professionals refine large-scale automation strategies.
Why this matters: Ansible skills remain valuable across roles and experience levels.
FAQs – People Also Ask
What are Ansible Trainers In Bangalore?
Professionals who provide hands-on Ansible training locally.
Why this matters: Local expertise increases relevance.
Is Ansible training suitable for DevOps roles?
Yes, DevOps depends heavily on automation.
Why this matters: Automation drives delivery efficiency.
Can beginners join Ansible training?
Yes, trainers start with foundational concepts.
Why this matters: Strong basics support growth.
Does training include real-world projects?
Yes, practical scenarios are included.
Why this matters: Practice builds confidence.
Is Ansible useful for cloud environments?
Yes, Ansible integrates with cloud platforms.
Why this matters: Cloud adoption continues to grow.
Does Ansible work with CI/CD pipelines?
Yes, pipelines trigger automation workflows.
Why this matters: CI/CD requires consistency.
Is Ansible helpful for SREs?
Yes, SREs automate reliability operations.
Why this matters: Reliability protects services.
Does Ansible reduce configuration drift?
Yes, automation enforces consistency.
Why this matters: Drift causes incidents.
Is certification valuable?
Yes, certification validates automation skills.
Why this matters: Validation builds trust.
Are Ansible skills in demand in Bangalore?
Yes, companies actively seek automation talent.
Why this matters: Demand supports career growth.
Branding & Authority
DevOpsSchool is a globally trusted training platform delivering enterprise-grade DevOps and automation education. Through structured curricula, hands-on labs, and production-focused learning, professionals gain job-ready skills aligned with modern IT demands. The Ansible Trainers In Bangalore program focuses on practical automation expertise required by Bangalore’s technology ecosystem.
Why this matters: Trusted platforms strengthen credibility and industry alignment.
Rajesh Kumar brings more than 20 years of hands-on experience across DevOps & DevSecOps, Site Reliability Engineering (SRE), DataOps, AIOps & MLOps, Kubernetes & Cloud Platforms, and CI/CD & Automation. His mentoring style emphasizes clarity, scalability, and production-ready automation outcomes.
Why this matters: Experienced leadership ensures enterprise-ready learning results.
Call to Action & Contact Information
Build practical Ansible automation expertise with guidance from experienced trainers in Bangalore.
Email: [email protected]
Phone & WhatsApp (India): +91 84094 92687
Phone & WhatsApp (USA): +1 (469) 756-6329




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reporter

GoBruteforcer Botnet Targets Crypto Project Databases by Exploiting Weak Credentials

A new wave of GoBruteforcer attacks has targeted databases of cryptocurrency and blockchain projects to co-opt them into a botnet that's capable of brute-forcing user passwords for services such as FTP, MySQL, PostgreSQL, and phpMyAdmin on Linux servers. "The current wave of campaigns is driven by two factors: the mass reuse of AI-generated server deployment examples that propagate commonView the full article
Hacker News

Become Enterprise Ready with Certified AiOps Trainers

Introduction: Problem, Context & Outcome
Modern enterprises run highly distributed systems across cloud, containers, and microservices. However, while system complexity increases, many engineers still depend on manual monitoring and reactive troubleshooting. Consequently, teams face alert overload, slow root cause analysis, and repeated incidents that impact availability. As data volumes grow, traditional operations models fail to provide timely insights or proactive control.
This growing gap makes AiOps Trainers essential in today’s technology landscape. Artificial Intelligence for IT Operations enables teams to analyze massive operational datasets and identify patterns that humans cannot process manually. However, organizations often fail to realize these benefits without experienced trainers who can translate theory into operational practice.
By reading this guide, professionals will understand the role of AiOps trainers, how they support DevOps delivery, and how expert training accelerates intelligent operations adoption. Why this matters: because proactive, data-driven operations reduce outages, noise, and operational risk.
What Is AiOps Trainers?
AiOps Trainers are specialists who teach engineers and IT teams how to apply artificial intelligence and machine learning within operational environments. Rather than focusing only on tools, they explain how data, algorithms, and workflows work together to improve IT operations.
In DevOps and cloud-native contexts, AiOps trainers guide learners through real operational use cases such as anomaly detection, event correlation, forecasting, and automated remediation. They help teams understand how AI models analyze logs, metrics, alerts, and traces generated by modern platforms.
Real-world relevance defines the value of AiOps training. Trainers bridge the gap between raw AI concepts and day-to-day operational decisions. Why this matters: because without skilled trainers, AiOps remains theoretical instead of transformational.
Why AiOps Trainers Is Important in Modern DevOps & Software Delivery
Modern DevOps emphasizes speed, automation, and continuous delivery. However, speed also amplifies operational complexity. Continuous deployments generate constant telemetry, and traditional monitoring tools struggle to keep up. As a result, teams miss early warning signals hidden in data.
AiOps trainers enable DevOps teams to use AI for smarter operations. They demonstrate how AI detects abnormal deployments in CI/CD pipelines and how predictive models forecast failures in cloud environments. Moreover, trainers align AiOps practices with Agile and DevOps principles by enabling faster feedback loops.
As organizations scale, AiOps becomes a necessity rather than an option. Why this matters: because intelligent operations sustain DevOps velocity without sacrificing reliability.
Core Concepts & Key Components
Operational Data Ingestion
Purpose: Centralize operational data for analysis.
How it works: AiOps platforms ingest logs, metrics, events, and traces.
Where it is used: Cloud platforms, applications, and pipelines.
Anomaly Detection Models
Purpose: Identify abnormal system behavior automatically.
How it works: Machine learning models detect deviations from normal patterns.
Where it is used: Performance monitoring and early incident detection.
Event Correlation Engines
Purpose: Reduce alert noise and identify relationships.
How it works: AI correlates multiple alerts into meaningful incidents.
Where it is used: Incident management systems.
Root Cause Identification
Purpose: Explain why incidents occur.
How it works: Models analyze dependencies and historical data.
Where it is used: Troubleshooting and postmortems.
Predictive and Prescriptive Analytics
Purpose: Prevent problems before they happen.
How it works: Trend analysis forecasts capacity and performance risks.
Where it is used: Reliability planning and optimization.
Why this matters: because these core elements convert operational chaos into actionable intelligence.
How AiOps Trainers Works (Step-by-Step Workflow)
AiOps trainers begin by introducing core concepts and operational data sources. Next, learners understand how AI processes telemetry collected from applications, infrastructure, and CI/CD pipelines. Then, trainers walk through anomaly detection and alert correlation using realistic DevOps scenarios.
Afterward, learners apply root cause analysis techniques to simulated incidents. Trainers also demonstrate how AiOps integrates with automation to trigger responses. Finally, evaluations focus on operational understanding instead of algorithm development.
This learning flow mirrors real DevOps operational lifecycles. Why this matters: because hands-on workflows ensure real adoption rather than surface knowledge.
Real-World Use Cases & Scenarios
Enterprises use AiOps to reduce mean time to resolution by correlating alerts across platforms. DevOps teams detect flawed deployments early using anomaly detection. SREs apply predictive insights to prevent outages during peak traffic.
Cloud teams optimize resource usage through forecasting models. QA teams gain faster feedback when test environments show unusual behavior. Businesses benefit through improved uptime and user experience. Why this matters: because AiOps directly impacts operational efficiency and customer trust.
Benefits of Using AiOps Trainers
Productivity: Faster analysis and incident response Reliability: Predictive insights reduce outages Scalability: AI handles operational complexity at scale Collaboration: Shared understanding across DevOps, SRE, and cloud teams Why this matters: because skilled training unlocks the real value of AiOps platforms.
Challenges, Risks & Common Mistakes
Teams often expect AiOps to work without clean data. Others assume AI replaces engineers completely. Some also skip model tuning and ignore context.
AiOps trainers address these risks by emphasizing data quality, human oversight, and continuous improvement. Why this matters: because misuse of AiOps increases noise instead of reducing it.
Comparison Table
AspectTraditional OperationsAiOps-Driven OperationsAlert HandlingManualAutomatedIncident DetectionReactivePredictiveRoot Cause AnalysisSlowAcceleratedData ProcessingLimitedScalableNoise ReductionWeakIntelligentAutomationScript-basedAI-assistedCloud ReadinessPartialFullScalabilityLowHighReliabilityInconsistentConsistentDecision MakingExperience-drivenData-driven Why this matters: because AiOps fundamentally modernizes IT operations.
Best Practices & Expert Recommendations
Teams should begin with centralized observability data. They should introduce AiOps incrementally and track measurable outcomes. Trainers also recommend aligning AiOps with SRE error budgets and automation.
Consistent evaluation ensures models evolve with systems. Why this matters: because disciplined adoption delivers sustainable results.
Who Should Learn or Use AiOps Trainers?
Developers gain insight into operational impact. DevOps engineers enhance monitoring and automation. SREs strengthen reliability strategies. Cloud and QA professionals improve system awareness.
Beginners learn foundational concepts, while senior engineers optimize complex systems. Why this matters: because AiOps skills support every delivery role.
FAQs – People Also Ask
What are AiOps Trainers?
They teach AI-driven IT operations practices.
Why this matters: because expertise accelerates adoption.
Is AiOps suitable for beginners?
Yes, when guided properly.
Why this matters: because structure prevents confusion.
Does AiOps replace operations teams?
No, it augments human decisions.
Why this matters: because humans remain critical.
Is AiOps relevant to DevOps teams?
Yes, it enhances CI/CD feedback.
Why this matters: because DevOps depends on insight.
Can SREs use AiOps effectively?
Yes, it supports reliability goals.
Why this matters: because uptime matters.
Does AiOps work in cloud systems?
Yes, it scales naturally.
Why this matters: because cloud complexity grows fast.
Is coding required for AiOps?
Understanding workflows matters more than code.
Why this matters: because accessibility matters.
Does AiOps reduce alert fatigue?
Yes, through correlation and filtering.
Why this matters: because noise delays response.
Is AiOps enterprise-ready?
Yes, enterprises adopt it widely.
Why this matters: because scale demands intelligence.
Do tools alone ensure success?
No, training remains essential.
Why this matters: because skills drive outcomes.
Branding & Authority
DevOpsSchool functions as a globally trusted provider of enterprise-ready DevOps and AI-driven operations education. Through DevOpsSchool, professionals access structured learning paths, including offerings delivered by AiOps Trainers, that emphasize real-world adoption and scalable practices. The platform prioritizes production relevance and long-term skill development. Why this matters: because credible platforms ensure learning effectiveness.
Rajesh Kumar brings more than 20 years of hands-on experience across DevOps, DevSecOps, Site Reliability Engineering, DataOps, AIOps, MLOps, Kubernetes, cloud platforms, and CI/CD automation. Through Rajesh Kumar, learners receive mentorship rooted in real enterprise operations and system-level thinking. Why this matters: because experienced guidance converts knowledge into capability.
Call to Action & Contact Information
Email: [email protected]
Phone & WhatsApp (India): +91 84094 92687
Phone & WhatsApp (USA): +1 (469) 756-6329




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Traefik Certification Guide for Kubernetes Engineers

Introduction: Problem, Context & Outcome
Today’s engineering teams rapidly release applications using containers, Kubernetes, and microservices. However, as services scale and change dynamically, managing incoming traffic becomes complex and risky. Engineers often face broken ingress rules, unpredictable routing behavior, and manual load balancer configurations that do not adapt to frequent deployments. Consequently, downtime, latency spikes, and security gaps affect production systems.
This reality makes Traefik Course Training and Certification critically important in modern DevOps environments. Traefik offers a cloud-native solution that automatically manages application traffic without constant manual intervention. Therefore, teams gain better control, visibility, and reliability across environments.
By reading this guide, learners will understand Traefik’s role in DevOps delivery, how training builds production-ready skills, and why certification matters for real-world success. Why this matters: because modern applications depend on reliable, automated traffic management.
What Is Traefik Course Training and Certification?
Traefik Course Training and Certification is a structured learning program that teaches engineers how to manage application traffic effectively in cloud-native infrastructures. The course focuses on Traefik as a modern reverse proxy, load balancer, and Kubernetes ingress controller built for dynamic environments.
Unlike traditional traffic management tools, Traefik automatically discovers services through container and orchestration platforms. The training explains how Traefik uses service metadata, labels, and providers to route traffic intelligently without static configuration files.
Developers and DevOps engineers use Traefik to expose services, manage secure access, and balance traffic across multiple instances. Therefore, the certification validates practical skills required to run Traefik confidently in production systems. Why this matters: because cloud-native infrastructure demands adaptive and intelligent routing solutions.
Why Traefik Course Training and Certification Is Important in Modern DevOps & Software Delivery
Modern DevOps practices emphasize automation, scalability, and rapid delivery. However, traditional load balancers struggle to handle dynamic services created and destroyed during CI/CD deployments. As a result, teams face configuration drift and slower release cycles.
Traefik integrates directly with CI/CD pipelines, container platforms, and Kubernetes clusters. It updates routing rules automatically as services change, which reduces manual effort and human error. Additionally, Traefik aligns well with Agile practices by enabling fast feedback and continuous deployment.
Organizations adopt Traefik to simplify ingress management, enforce security policies, and maintain high availability. Why this matters: because automated traffic routing directly supports DevOps speed and system reliability.
Core Concepts & Key Components
Dynamic Service Discovery
Purpose: Detect backend services automatically.
How it works: Traefik listens to providers like Docker and Kubernetes.
Where it is used: Microservices and containerized environments.
Reverse Proxy Functionality
Purpose: Handle incoming requests and forward them correctly.
How it works: Traefik routes traffic to the appropriate service instance.
Where it is used: API gateways and production applications.
Load Balancing Mechanism
Purpose: Distribute traffic evenly across services.
How it works: Traefik balances requests using intelligent algorithms.
Where it is used: High-traffic systems and scalable applications.
Kubernetes Ingress Controller
Purpose: Control external access to Kubernetes services.
How it works: Traefik processes ingress resources dynamically.
Where it is used: Kubernetes-based deployments.
Security, TLS, and Middleware
Purpose: Secure and control traffic flows.
How it works: Traefik automates TLS certificates and enforces middleware rules.
Where it is used: Public-facing applications and APIs.
Why this matters: because understanding these components ensures stable, secure, and scalable traffic handling.
How Traefik Course Training and Certification Works (Step-by-Step Workflow)
The training begins with Traefik architecture and core concepts. Next, learners explore how Traefik integrates with Docker and Kubernetes providers. Then, the course explains routing rules, entry points, and middleware configuration.
After that, learners focus on TLS automation, security policies, and observability features. The course also demonstrates how Traefik works within CI/CD pipelines to support continuous deployments and rolling updates.
Finally, practical assessments evaluate applied knowledge through real-world scenarios. Why this matters: because step-by-step learning mirrors the actual DevOps lifecycle.
Real-World Use Cases & Scenarios
DevOps teams deploy Traefik to manage ingress traffic in Kubernetes clusters. Developers use it locally to test routing behavior before production. QA teams validate routing and security configurations during testing cycles.
SRE teams rely on Traefik to maintain availability and monitor traffic patterns. Cloud engineers use it in multi-region deployments to ensure consistent access. Businesses benefit from reduced downtime and faster releases. Why this matters: because real-world systems demand dependable traffic control.
Benefits of Using Traefik Course Training and Certification
Productivity: Faster deployments with automatic routing Reliability: Consistent traffic handling during scaling events Scalability: Seamless support for cloud-native growth Collaboration: Shared routing practices across teams Why this matters: because certified knowledge turns Traefik into a stable production asset.
Challenges, Risks & Common Mistakes
Many engineers misconfigure routing rules or overlook middleware security. Others rely on default settings without understanding traffic behavior. Some teams also ignore monitoring and logs.
The training helps mitigate these risks by teaching best practices and real deployment lessons. Why this matters: because small routing mistakes can cause large outages.
Comparison Table
AspectTraditional Load BalancersTraefikConfigurationStaticDynamicKubernetes IntegrationLimitedNativeService DiscoveryManualAutomaticTLS ManagementComplexAutomatedCI/CD SupportMinimalStrongScalabilityManualAutomaticObservabilityBasicAdvancedCloud-Native DesignPartialFullMaintenance EffortHighLowDeployment SpeedSlowFast Why this matters: because adaptive tools outperform legacy approaches in dynamic environments.
Best Practices & Expert Recommendations
Teams should define routing rules clearly and use consistent labels. Engineers should enable TLS automation early and monitor traffic continuously. Additionally, staged rollouts and testing reduce deployment risk.
The course promotes scalable, secure, and maintainable Traefik configurations. Why this matters: because best practices ensure long-term reliability.
Who Should Learn or Use Traefik Course Training and Certification?
Developers deploying containerized apps gain immediate value. DevOps engineers strengthen ingress and routing expertise. Cloud engineers, SREs, and QA professionals enhance reliability and testing workflows.
Beginners learn foundations, while experienced engineers refine production-grade strategies. Why this matters: because Traefik skills apply across roles and experience levels.
FAQs – People Also Ask
What is Traefik Course Training and Certification?
It validates practical Traefik traffic management skills.
Why this matters: because certification proves applied expertise.
Is Traefik suitable for beginners?
Yes, dynamic discovery simplifies setup.
Why this matters: because easy onboarding speeds adoption.
Is it useful for DevOps engineers?
Yes, it integrates with DevOps workflows.
Why this matters: because DevOps relies on automation.
Does Traefik support Kubernetes?
Yes, it functions as a native ingress controller.
Why this matters: because Kubernetes dominates cloud platforms.
Is TLS included in the training?
Yes, automated TLS forms a core topic.
Why this matters: because security is critical.
Can SREs use Traefik effectively?
Yes, it supports reliability objectives.
Why this matters: because uptime matters.
Does Traefik integrate with CI/CD?
Yes, routing updates occur automatically.
Why this matters: because speed matters.
Is certification valuable for careers?
Yes, it demonstrates cloud-native expertise.
Why this matters: because skills drive growth.
Does Traefik scale well?
Yes, it handles high traffic loads.
Why this matters: because growth requires scalability.
Is real-world practice included?
Yes, scenarios mirror production use.
Why this matters: because practice ensures readiness.
Branding & Authority
DevOpsSchool serves as a globally trusted platform for enterprise-ready DevOps and cloud education. Through DevOpsSchool, professionals access structured programs, including the Traefik Course Training and Certification, designed to build real production competence. The platform prioritizes practical learning, system thinking, and long-term skill development. Why this matters: because trusted platforms ensure learning quality.
Rajesh Kumar brings more than two decades of hands-on experience across DevOps, DevSecOps, Site Reliability Engineering, DataOps, AIOps, MLOps, Kubernetes, cloud platforms, and CI/CD automation. Through Rajesh Kumar, learners receive guidance grounded in real production challenges and scalable architectures. Why this matters: because expert mentorship accelerates mastery.
Call to Action & Contact Information
Email: [email protected]
Phone & WhatsApp (India): +91 7004215841
Phone & WhatsApp (USA): +1 (469) 756-6329




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reporter

Iran-linked MuddyWater APT deploys Rust-based implant in latest campaign

Iran-linked advanced persistent threat group MuddyWater has deployed a Rust-based implant in an ongoing espionage campaign targeting organizations in Israel and other Middle Eastern countries, according to CloudSEK.
CloudSEK’s TRIAD team said it identified the spear-phishing campaign targeting diplomatic, maritime, financial, and telecom entities across the Middle East. The campaign uses icon spoofing and malicious Word documents to deliver RustyWater, which the researchers described as “a Rust-based implant representing a significant upgrade to their traditional toolkit.”
“Historically, Muddy Water has relied on PowerShell and VBS loaders for initial access and post-compromise operations,” the cybersecurity firm wrote in a blog post. “The introduction of Rust-based implants represents a notable tooling evolution toward more structured, modular, and low noise RAT capabilities.”
MuddyWater, which Microsoft tracks as Mango Sandstorm and ProofPoint identifies as TA450, operates under Iran’s Ministry of Intelligence and Security, according to the US cybersecurity agency CISA. The group has been active since at least 2017, targeting government agencies, telecommunications providers, and critical infrastructure across the Middle East, Asia, and Europe, according to security firms.
The research comes amid continued activity by MuddyWater throughout 2024 and into early 2025. ESET researchers published findings in December 2024 showing the group deployed the MuddyViper backdoor against Israeli organizations between September 2024 and March 2025. Security firms have also documented MuddyWater deploying BugSleep implants and using legitimate remote monitoring and management tools in recent campaigns.
Spear-phishing delivery
The attack chain begins with spear-phishing emails containing malicious ZIP archives, according to the blog post. The archives include a legitimate PDF document and a disguised executable file bearing a PDF icon. When victims execute the file, it displays the decoy PDF while executing the malware, the researchers wrote.
They wrote that the initial loader establishes persistence through Windows Registry modifications and deploys RustyWater as a secondary payload. The implant communicates with command-and-control infrastructure using HTTP/HTTPS protocols and supports file system enumeration, command execution, and data exfiltration.
CloudSEK identified command-and-control domains mimicking legitimate services, including infrastructure posing as Dropbox and WordPress platforms. Several domains were registered through Hostinger, a hosting provider the cybersecurity firm said has been frequently abused by threat actors.
Rust offers evasion advantages
CloudSEK researchers said RustyWater was developed in Rust, which they said is increasingly used by malware authors for its memory safety features and cross-platform capabilities, according to the blog post. Other state-sponsored groups, including Russia’s Gossamer Bear and China-linked actors, have also deployed Rust-based malware in recent campaigns, according to security researchers.
The implant incorporates checks for virtual machine environments, debugging tools, and sandbox systems. “RustyWater begins execution by establishing anti-debugging and anti-tampering mechanisms,” the researchers wrote. “It registers a Vectored Exception Handler (VEH) to catch debugging attempts and systematically gathers victim machine information, including username, computer name, and domain membership.”
RustyWater also uses string obfuscation and multi-stage payload delivery, the researchers said. The malware encrypts all strings using position-independent XOR encryption and implements randomized sleep intervals between command-and-control callbacks to avoid detection, according to the blog post.
Broader targeting
CloudSEK said its investigation primarily focused on targeting within Israel, but the researchers observed indicators suggesting MuddyWater may have expanded operations to include victims in India, the UAE, and other countries in the region.
The campaign targeting Israeli entities used Hebrew-language decoy documents related to government agencies and the Israel Defense Forces, the blog post added.
MuddyWater has focused on espionage operations aimed at collecting government and military intelligence, according to security researchers. Previous campaigns attributed to the group used various remote access tools and custom malware families, including the PhonyC2 command-and-control framework and legitimate remote administration tools like SimpleHelp.
In November 2024, Amazon Threat Intelligence correlated MuddyWater activity with subsequent missile strikes, showing the group accessed compromised servers containing live CCTV feeds prior to attacks in Israel and the Red Sea. CloudSEK recommended organizations implement email security controls, conduct security awareness training to help employees identify phishing attempts, and deploy endpoint detection and response solutions capable of identifying suspicious process behavior and network communications patterns.
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CSOonline

TOEFL Exam Preparation Training: Study Guide for Success

Introduction: Problem, Context & Outcome
Many engineers and technology professionals face a silent career barrier. While they possess strong technical knowledge, limited English proficiency restricts global education, overseas jobs, and international collaboration. Consequently, talented professionals miss opportunities despite having the required technical skills. Meanwhile, universities and global employers increasingly demand proof of English proficiency through standardized exams.
Therefore, the TOEFL Exam Preparation Traning course plays a critical role today. It enables learners to demonstrate English competency in reading, listening, speaking, and writing through a globally accepted assessment. At the same time, it builds confidence for academic and professional environments.
Through structured preparation, learners gain exam clarity, strong communication skills, and measurable results. As a result, they unlock global academic and career opportunities with confidence. Why this matters: global success requires proven communication ability, not assumptions.
What Is TOEFL Exam Preparation Traning course?
The TOEFL Exam Preparation Traning course is a structured program designed to help learners achieve strong scores in the TOEFL examination. It focuses on exam-specific strategies rather than general English learning alone. Learners train across all four sections—Reading, Listening, Speaking, and Writing—using proven techniques aligned with exam patterns.
Additionally, the course explains the TOEFL format, scoring logic, question types, and time constraints. Because of this clarity, learners avoid confusion and reduce exam stress. Instead of guessing answers, they follow structured response frameworks.
Although TOEFL often supports academic goals, professionals in software development, DevOps, and cloud engineering also benefit. Global teams demand clear English communication in meetings, documentation, and collaboration. Why this matters: English proficiency directly influences global career mobility and academic admission success.
Why TOEFL Exam Preparation Traning course Is Important in Modern DevOps & Software Delivery
Modern DevOps and software delivery environments operate globally. Engineers collaborate across regions, cultures, and time zones. Therefore, English communication becomes a core professional skill alongside technical ability.
The TOEFL Exam Preparation Traning course helps DevOps Engineers, developers, and cloud professionals prepare for international opportunities. It strengthens listening comprehension for global calls, structured writing for documentation, and confident speaking for reviews and presentations.
Moreover, Agile ceremonies, CI/CD documentation, cloud architecture discussions, and incident reports rely heavily on clear English. Weak communication slows delivery and increases errors. Why this matters: strong English skills enhance delivery speed, collaboration quality, and professional credibility.
Core Concepts & Key Components
TOEFL Reading Skills
Purpose: Build strong academic comprehension
How it works: Learners practice timed reading passages and question strategies
Where it is used: Academic coursework and technical documentation
TOEFL Listening Skills
Purpose: Improve understanding of spoken English
How it works: Candidates practice lectures and conversations with analysis
Where it is used: Meetings, training sessions, and remote collaboration
TOEFL Speaking Skills
Purpose: Develop confident verbal responses
How it works: Structured templates guide clear spoken answers
Where it is used: Interviews, presentations, and team discussions
TOEFL Writing Skills
Purpose: Strengthen academic writing structure
How it works: Learners follow response frameworks with feedback
Where it is used: Reports, essays, and technical proposals
Vocabulary and Grammar Foundation
Purpose: Improve accuracy and clarity
How it works: Targeted practice corrects common errors
Where it is used: Daily professional communication
Why this matters: each component supports real-world communication while improving exam performance.
How TOEFL Exam Preparation Traning course Works (Step-by-Step Workflow)
First, learners assess their current English level through diagnostic evaluations. Next, the course explains the TOEFL structure, scoring model, and timing strategy. This early clarity reduces anxiety and builds focus.
Then, learners practice each section independently using structured techniques. Reading and listening improve comprehension speed, while speaking and writing strengthen clarity and organization. Trainers provide corrections and improvement guidance continuously.
Finally, full-length mock exams simulate real test conditions. Regular review helps learners track progress and adjust strategies before the final exam. Why this matters: step-by-step preparation replaces trial-and-error learning.
Real-World Use Cases & Scenarios
Software engineers use TOEFL scores to apply for global universities and international certifications. DevOps Engineers rely on TOEFL results to qualify for overseas roles in multinational organizations.
Cloud Engineers and SREs benefit through improved listening and speaking during global incident calls and architecture reviews. QA professionals use enhanced writing skills for documentation and reporting.
Across roles, strong English improves collaboration, delivery speed, and professional trust. Why this matters: communication quality directly affects technical effectiveness and global career growth.
Benefits of Using TOEFL Exam Preparation Traning course
Productivity: Faster comprehension and expression Reliability: Consistent communication during exams and work Scalability: Readiness for global education and teams Collaboration: Clear interaction with international peers Why this matters: strong communication multiplies technical impact.
Challenges, Risks & Common Mistakes
Many learners rely on generic English practice instead of exam-focused strategies. Consequently, scores remain stagnant despite effort. Others ignore time management, which leads to incomplete sections.
Additionally, learners often skip structured feedback for speaking and writing. Without correction, mistakes repeat. Guided training and mock exams reduce these risks effectively. Why this matters: avoiding common errors saves time, money, and exam attempts.
Comparison Table
AspectSelf PracticeTOEFL Exam Preparation Traning courseExam StrategyRandomStructuredFeedbackLimitedExpert-guidedSpeaking PracticeRareRegularWriting ReviewAbsentDetailedConfidence LevelLowHighTime ManagementWeakStrongAccuracyInconsistentConsistentProgress TrackingNoneContinuousMock ExamsOccasionalFrequentResult PredictabilityLowHigh Why this matters: structured training produces predictable results.
Best Practices & Expert Recommendations
Start preparation early and follow a disciplined schedule. Practice timed tests consistently. Review feedback immediately and apply corrections.
Additionally, balance focus across all four sections instead of favoring strengths. Regular mock exams and revision ensure steady improvement. Why this matters: disciplined habits lead to reliable score improvement.
Who Should Learn or Use TOEFL Exam Preparation Traning course?
Developers planning overseas education gain immediate value. DevOps Engineers targeting global roles improve communication confidence. Cloud Engineers, SREs, and QA professionals benefit from clearer collaboration skills.
Both beginners and experienced professionals succeed with structured preparation. Why this matters: TOEFL readiness supports long-term global career progression.
FAQs – People Also Ask
What is TOEFL Exam Preparation Traning course?
It prepares learners for all TOEFL sections effectively. Why this matters: structure improves scores.
Why is TOEFL important?
It validates English skills globally. Why this matters: institutions trust it.
Is it suitable for beginners?
Yes, with guided learning. Why this matters: clarity reduces confusion.
Does it help working professionals?
Yes, for global roles. Why this matters: communication drives success.
How long does preparation take?
It depends on skill level. Why this matters: planning saves time.
Is speaking difficult in TOEFL?
Practice makes it manageable. Why this matters: confidence improves fluency.
Does the course include mock exams?
Yes, full simulations. Why this matters: readiness improves accuracy.
Can DevOps Engineers benefit?
Yes, significantly. Why this matters: global teams need clarity.
Is grammar important for TOEFL?
Yes, for accuracy. Why this matters: precision matters.
Is TOEFL accepted worldwide?
Yes, globally. Why this matters: recognition opens doors.
Branding & Authority
DevOpsSchool operates as a trusted global training platform offering outcome-driven programs, including the TOEFL Exam Preparation Traning course. The platform emphasizes structured learning, real-world relevance, and measurable improvement. Learners receive expert guidance designed for academic and professional global success. Why this matters: credible platforms deliver reliable learning outcomes.
Rajesh Kumar brings more than 20 years of hands-on expertise across DevOps & DevSecOps, Site Reliability Engineering, DataOps, AIOps, MLOps, Kubernetes, Cloud Platforms, and CI/CD automation. His mentoring approach focuses on clarity, discipline, and real-world applicability. Why this matters: experienced mentorship reduces learning risk and accelerates success.
Call to Action & Contact Information
Begin your preparation with the TOEFL Exam Preparation Traning course and move confidently toward global education and professional opportunities.
Email: [email protected]
Phone & WhatsApp (India): +91 7004215841
Phone & WhatsApp (USA): +1 (469) 756-6329




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DevOps Engineering (MDE): Comprehensive Certification Guide

Introduction: Problem, Context & Outcome
Today’s engineering teams must deliver software at speed while protecting stability and security. However, many organizations still struggle because DevOps knowledge remains fragmented. Developers write code efficiently, operations teams manage infrastructure independently, and responsibility often remains divided. Because of this separation, deployment pipelines break, releases slow down, and production incidents rise. At the same time, cloud-native platforms, CI/CD automation, and DevOps-driven delivery models now demand engineers who can manage the entire lifecycle, not isolated tasks.
Therefore, the DevOps Engineering (MDE) Certification exists to close this gap. It validates practical DevOps engineering capability instead of surface-level tool familiarity. Consequently, learners gain structured knowledge, real-world confidence, and production-ready skills. Ultimately, readers understand how to build, deploy, operate, and improve systems reliably in modern environments.
Why this matters: Businesses now require engineers who own delivery outcomes, not just individual steps.
What Is DevOps Engineering (MDE) Certification?
The DevOps Engineering (MDE) Certification verifies an engineer’s ability to design, implement, and operate modern DevOps workflows across real production systems. Instead of centering on a single vendor or toolchain, it focuses on foundational DevOps engineering principles, automation-first practices, and operational ownership. Because modern DevOps roles demand broad responsibility, the certification integrates CI/CD, cloud infrastructure, monitoring, reliability, and security into one cohesive learning model.
Moreover, this certification mirrors how DevOps functions in enterprise environments. Engineers learn how changes flow from version control to production. They also learn how teams collaborate, detect failures early, and recover systems efficiently. Importantly, the certification evaluates applied understanding rather than memorized definitions.
As a result, software developers, DevOps engineers, and SREs use this certification to demonstrate real-world readiness across industries and team structures.
Why this matters: Employers value proven operational capability over theoretical knowledge.
Why DevOps Engineering (MDE) Certification Is Important in Modern DevOps & Software Delivery
Modern software delivery depends on automation, speed, and resilience. Because organizations deploy continuously, manual workflows no longer scale safely. The DevOps Engineering (MDE) Certification prepares engineers for these realities by emphasizing continuous delivery, cloud-native infrastructure, and reliability engineering practices.
Additionally, organizations adopt DevOps to remove silos and improve collaboration between teams. This certification reinforces shared accountability, measurable outcomes, and continuous improvement. It aligns closely with Agile development, CI/CD pipelines, microservices, and DevSecOps strategies that define modern software delivery.
Consequently, certified engineers reduce deployment risk, accelerate feedback loops, and improve system reliability. At the same time, they adapt quickly to new technologies because they understand core engineering concepts rather than transient tools.
Why this matters: Sustainable DevOps success depends on engineering fundamentals.
Core Concepts & Key Components
Continuous Integration & Continuous Delivery
Purpose: Enable rapid and reliable software delivery.
How it works: Engineers integrate code frequently while automated pipelines test, validate, and deploy changes.
Where it is used: Daily development workflows and production releases.
Infrastructure as Code
Purpose: Ensure consistency across environments.
How it works: Infrastructure definitions live in version control and deploy automatically.
Where it is used: Cloud provisioning and environment replication.
Cloud & Containerization
Purpose: Support scalability and portability.
How it works: Containers package applications, while cloud platforms allocate resources dynamically.
Where it is used: Microservices and distributed systems.
Monitoring & Observability
Purpose: Provide insight into system behavior.
How it works: Metrics, logs, and alerts expose performance and failures.
Where it is used: Production operations and incident management.
DevSecOps Practices
Purpose: Embed security into delivery workflows.
How it works: Automated security checks execute within CI/CD pipelines.
Where it is used: Secure software releases.
Collaboration & Workflow Design
Purpose: Align teams toward shared delivery goals.
How it works: Ownership models, automation, and feedback loops guide collaboration.
Where it is used: Cross-functional DevOps organizations.
Why this matters: These components form the backbone of dependable DevOps engineering.
How DevOps Engineering (MDE) Certification Works (Step-by-Step Workflow)
First, learners establish a strong foundation in DevOps concepts and delivery models. Next, they apply these principles to CI/CD pipelines, infrastructure automation, and cloud environments. Afterward, they design practical solutions for deployments, monitoring, scaling, and recovery scenarios.
Then, the certification evaluates understanding through real-world scenarios instead of abstract questions. Rather than testing syntax, it assesses engineering judgment and operational reasoning. Finally, learners demonstrate end-to-end DevOps capability aligned with production systems.
Throughout the journey, learning remains tied to realistic DevOps lifecycle challenges.
Why this matters: Structured workflows ensure learning transfers directly to job performance.
Real-World Use Cases & Scenarios
High-growth technology companies depend on DevOps engineers to enable continuous deployment. Development teams automate builds and releases, while QA teams integrate testing into pipelines. Meanwhile, cloud teams scale infrastructure automatically during demand spikes.
SRE teams use monitoring and observability to reduce downtime and improve availability. As a result, organizations gain predictable releases, faster recovery, and improved customer trust. Additionally, enterprises adopting microservices rely on DevOps engineers to manage container orchestration and deployment strategies effectively.
Why this matters: Real-world scenarios prove measurable business value.
Benefits of Using DevOps Engineering (MDE) Certification
Productivity: Faster delivery with fewer manual steps Reliability: Stable systems and predictable releases Scalability: Efficient cloud and container management Collaboration: Better alignment across engineering teams Career Growth: Increased credibility in DevOps roles Why this matters: These benefits directly impact engineering success and business outcomes.
Challenges, Risks & Common Mistakes
Many teams focus excessively on tools instead of workflows. Additionally, organizations sometimes delay automation, leading to fragile pipelines. Others neglect monitoring and security until failures occur, increasing operational risk.
However, this certification addresses these pitfalls by reinforcing fundamentals, automation-first thinking, and proactive reliability practices. Engineers learn how to prevent issues rather than respond to emergencies.
Why this matters: Avoiding common mistakes protects systems and reputations.
Comparison Table
Traditional ITModern DevOps (MDE)Manual deploymentsAutomated CI/CD pipelinesIsolated teamsCross-functional collaborationStatic infrastructureInfrastructure as CodeInfrequent releasesContinuous deliveryReactive monitoringProactive observabilityTool-based learningEngineering-based learningLimited scalabilityCloud-native scalabilitySeparate security stepsIntegrated DevSecOpsSlow feedbackRapid feedback loopsHigh release riskControlled rollbacks Why this matters: Clear contrasts highlight DevOps advantages.
Best Practices & Expert Recommendations
Begin with automation at the earliest stages. Additionally, version everything, including infrastructure and pipelines. Implement monitoring early and review metrics consistently.
Furthermore, encourage shared ownership across teams and refine workflows continuously based on feedback. Finally, master core principles before adopting advanced tools.
Why this matters: Best practices sustain long-term DevOps maturity.
Who Should Learn or Use DevOps Engineering (MDE) Certification?
Software developers gain operational insight and delivery awareness. DevOps engineers strengthen end-to-end system ownership. Cloud engineers, SREs, and QA professionals benefit through automation, reliability, and scalability knowledge.
Both beginners and experienced professionals benefit equally. Beginners build strong foundations, while experienced engineers formalize and validate existing skills.
Why this matters: DevOps expertise applies across multiple technical roles.
FAQs – People Also Ask
What is DevOps Engineering (MDE) Certification?
It validates practical DevOps engineering skills.
Why this matters: Employers trust applied competence.
Is it suitable for beginners?
Yes, it builds skills progressively.
Why this matters: Structured learning prevents gaps.
Does it focus on tools?
It emphasizes principles over tools.
Why this matters: Principles remain stable over time.
Is it relevant for DevOps jobs?
Yes, it aligns with real roles.
Why this matters: Relevance improves hiring outcomes.
Does it include cloud and CI/CD?
Yes, both serve as core topics.
Why this matters: Modern delivery depends on them.
Can developers take this certification?
Yes, developers gain delivery ownership insight.
Why this matters: DevOps requires shared responsibility.
Is it enterprise-focused?
Yes, it supports large-scale systems.
Why this matters: Enterprises need scalable solutions.
How does it compare to vendor certifications?
It remains vendor-neutral.
Why this matters: Neutral skills age better.
Does it support career growth?
Yes, it improves professional credibility.
Why this matters: Credibility accelerates opportunities.
Is it aligned with SRE practices?
Yes, it includes reliability concepts.
Why this matters: Reliability builds customer trust.
Branding & Authority
DevOpsSchool serves as a globally trusted DevOps learning platform delivering enterprise-grade training and certifications. Through structured learning paths, hands-on labs, and production-aligned curricula, professionals gain practical DevOps engineering skills that reflect real industry needs.
Why this matters: Trusted platforms ensure credible, job-ready learning.
Rajesh Kumar brings more than two decades of hands-on experience across DevOps, DevSecOps, Site Reliability Engineering (SRE), DataOps, AIOps, MLOps, Kubernetes, cloud platforms, and CI/CD automation. His mentorship ensures learners gain production-tested, enterprise-relevant expertise.
Why this matters: Experienced guidance ensures real-world readiness.
Call to Action & Contact Information
Explore the DevOps Engineering (MDE) Certification and build enterprise-ready DevOps engineering skills aligned with modern delivery practices.
Email: [email protected]
Phone & WhatsApp (India): +91 7004215841
Phone & WhatsApp (USA): +1 (469) 756-6329




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Anthropic Launches Claude AI for Healthcare with Secure Health Record Access

Anthropic has become the latest Artificial intelligence (AI) company to announce a new suite of features that allows users of its Claude platform to better understand their health information. Under an initiative called Claude for Healthcare, the company said U.S. subscribers of Claude Pro and Max plans can opt to give Claude secure access to their lab results and health records by connecting toView the full article
Hacker News

Dobrindt: Mehr Kooperation mit Israel für Sicherheit Deutschlands

ekavector – shutterstock.com
Angesichts der wachsenden Gefahr von Angriffen will die Bundesrepublik ihre Zusammenarbeit mit Israel im Sicherheitsbereich ausbauen. Ziel sei mehr Schutz für Deutschland, sagte Bundesinnenminister Alexander Dobrindt (CSU) bei einem Besuch in Israel. Er unterzeichnete zusammen mit dem israelischen Ministerpräsidenten Benjamin Netanjahu einen Cyber- und Sicherheitspakt. 
Konkret geht es unter anderem um eine enge Vernetzung der Sicherheitsbehörden beider Länder sowie um eine noch engere Kooperation in den Bereichen Cyberkriminalität, Künstliche Intelligenz (KI) und Drohnenabwehr, wie Dobrindt vor Medienvertretern in Jerusalem sagte. Deutschland wolle dabei die Erfahrungen und Technologien Israels nutzen. Es gebe immer mehr potenzielle Gruppen, die etwa Infrastruktur-Einrichtungen angreifen könnten.
Netanjahu sagte, Cyberangriffe seien eine der größten Bedrohungen für die innere Sicherheit. Neben der gemeinsamen Cyberabwehr gehe es bei der “umfassenden Sicherheitspartnerschaft” zwischen Deutschland und Israel aber auch um Terrorismusbekämpfung. “Der Iran und seine Verbündeten – Hisbollah, Hamas und Huthis – bedrohen nicht nur Israel, sondern auch die regionale Stabilität und die internationale Sicherheit”, sagte der israelische Regierungschef weiter.
Deutschland will auch Israels Sicherheit mit gewährleisten
Dobrindt erklärte, Deutschland werde zudem erstmals beim US-geführten Büro des Sicherheitskoordinators für Israel und die Palästinensische Autonomiebehörde (OSC) in Jerusalem “mit in die Führung” gehen. Diese Funktion werde der bisherige Präsident der Spezialkräfte der Polizei in Deutschland, Olaf Lindner, übernehmen. 
Deutschland unterstützt schon seit vielen Jahren die Polizei in den palästinensischen Gebieten, um dort zur Stabilisierung der Lage beizutragen. Deutschland wolle Israels Sicherheit mit gewährleisten, sagte Dobrindt.
Die unterzeichnete Erklärung unterstreiche “Deutschlands großes Engagement für die Sicherheit des Staates Israel”, betonte Netanjahu.
Der deutsche Innenminister hatte zuvor auch Israels Außenminister Gideon Saar getroffen. (dpa/jm)

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CSOonline

Dobrindt: Mehr Kooperation mit Israel für Sicherheit Deutschlands

ekavector – shutterstock.com
Angesichts der wachsenden Gefahr von Angriffen will die Bundesrepublik ihre Zusammenarbeit mit Israel im Sicherheitsbereich ausbauen. Ziel sei mehr Schutz für Deutschland, sagte Bundesinnenminister Alexander Dobrindt (CSU) bei einem Besuch in Israel. Er unterzeichnete zusammen mit dem israelischen Ministerpräsidenten Benjamin Netanjahu einen Cyber- und Sicherheitspakt. 
Konkret geht es unter anderem um eine enge Vernetzung der Sicherheitsbehörden beider Länder sowie um eine noch engere Kooperation in den Bereichen Cyberkriminalität, Künstliche Intelligenz (KI) und Drohnenabwehr, wie Dobrindt vor Medienvertretern in Jerusalem sagte. Deutschland wolle dabei die Erfahrungen und Technologien Israels nutzen. Es gebe immer mehr potenzielle Gruppen, die etwa Infrastruktur-Einrichtungen angreifen könnten.
Netanjahu sagte, Cyberangriffe seien eine der größten Bedrohungen für die innere Sicherheit. Neben der gemeinsamen Cyberabwehr gehe es bei der “umfassenden Sicherheitspartnerschaft” zwischen Deutschland und Israel aber auch um Terrorismusbekämpfung. “Der Iran und seine Verbündeten – Hisbollah, Hamas und Huthis – bedrohen nicht nur Israel, sondern auch die regionale Stabilität und die internationale Sicherheit”, sagte der israelische Regierungschef weiter.
Deutschland will auch Israels Sicherheit mit gewährleisten
Dobrindt erklärte, Deutschland werde zudem erstmals beim US-geführten Büro des Sicherheitskoordinators für Israel und die Palästinensische Autonomiebehörde (OSC) in Jerusalem “mit in die Führung” gehen. Diese Funktion werde der bisherige Präsident der Spezialkräfte der Polizei in Deutschland, Olaf Lindner, übernehmen. 
Deutschland unterstützt schon seit vielen Jahren die Polizei in den palästinensischen Gebieten, um dort zur Stabilisierung der Lage beizutragen. Deutschland wolle Israels Sicherheit mit gewährleisten, sagte Dobrindt.
Die unterzeichnete Erklärung unterstreiche “Deutschlands großes Engagement für die Sicherheit des Staates Israel”, betonte Netanjahu.
Der deutsche Innenminister hatte zuvor auch Israels Außenminister Gideon Saar getroffen. (dpa/jm)

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CSOonline

Researchers Uncover Service Providers Fueling Industrial-Scale Pig Butchering Fraud

Cybersecurity researchers have shed light on two service providers that supply online criminal networks with the necessary tools and infrastructure to fuel the pig butchering-as-a-service (PBaaS) economy. At least since 2016, Chinese-speaking criminal groups have erected industrial-scale scam centers across Southeast Asia, creating special economic zones that are devoted to fraudulent investmentView the full article
Hacker News

CISOs’ top 10 cybersecurity priorities for 2026

Cybersecurity threats are becoming more sophisticated, more automated, and more intelligent, as well as harder to detect.
At the same time the enterprise attack surface CISOs are tasked to defend continues to expand.
That’s the reality security chiefs face in 2026 — a reality that has CISOs reordering their priorities for the year ahead.
Preparing for and defending against AI-enabled attacks is high on CISOs’ to-do list this year. As is securing their organization’s own AI deployments and advancing the use of AI in security operations.
Those priorities are in addition to many longstanding security undertakings as well as emerging areas of concern that will also dominate the CISO agenda in the upcoming year. Security leaders say these priorities reflect the ever-increasing challenges of defending their organizations.
Doubling down on core security tasks
Although AI has emerged as a top issue for security leaders, Foundry’s Security Priorities Survey recently found that CISOs remain focused on several core security tasks, with strengthening data protection the No. 1 priority, cited by 48% of security chiefs.
Amit Levinstein, who is both a CISO and a CISO advisor, specifically calls out data protection as a top priority for his own organization and his clients’ security departments.
Levinstein, CISO and vice president of professional services at cybersecurity firm CYE, acknowledges that data protection has been a key security task for a long time but says it has become more challenging in the age of AI, as the technology “creates a lot of different risks from a data leakage perspective.”
To counteract those risks, Levinstein relies on strong AI usage policies, robust AI governance, and employee training to establish and enforce when AI can be used and with what data and security controls.
To do this effectively, he says he and other CISOs must “understand what the business is doing, understand the business’ priorities and then devise the right approach.”
Other longstanding core security tasks CISOs list as top priorities include securing cloud data and systems, simplifying IT security infrastructure, and improving threat intelligence operations.
Other top 10 priorities from the Foundry survey include enhancing security awareness through end-user training; streamlining compliance and privacy efforts; reducing spending; and assuming responsibility for risks presented by operational technology systems, IoT devices, and/or endpoints.
Prepping for AI-enabled attacks
Although conventional tasks dominate the CISO priorities in the Foundry survey, interviews and other research show that AI-related issues are also high on the CISO priority list.
For example, 53% of security leaders ranked AI-enabled cyber threats as a top-three organizational risk in a global survey conducted by Boston Consulting Group. BCG also reported that 60% of organizations have likely experienced an AI-powered cyberattack in the past year, although only 7% have installed AI-driven cyber defense tools.
“Offense is scaling faster than defense. AI is accelerating attack capabilities far more quickly than organizations can strengthen their defenses,” BCG notes in its report.
While hype over AI-enabled threats has come under scrutiny, security experts warn that ignoring AI in the threat chain could be costly for CISOs, given the rise of real-world AI security threats in the wild.
Rolling out AI to enhance security operations
Although a sliver of organizations surveyed by BCG have deployed AI-driven cyber defense tools, the vast majority (88%) plan to implement them.
Foundry similarly found in its survey that 38% of security leaders listed accelerating use of AI to improve security effectiveness as a priority.
Aaron Momin, CISO of Synechron, a digital transformation consulting and solutions firm, sees AI as an essential security tool.
“CISOs are prioritizing AI systems that detect and neutralize cyber threats without humans in the loop to reduce the time to respond,” he says. “When AI-powered attacks hit in milliseconds, human-speed response is inadequate and requires AI to fight against AI.”
Momin also has prioritized deploying autonomous AI agents in security, noting that “these agents are expected to execute tasks on their own, such as automating access revocation based on risk factors or blocking the cyber threat before propagation. It comes down to speed. Attackers are using AI to iterate on their attacks faster than any human analyst can triage an alert.”
Securing enterprise AI deployments
Security experts say AI-enabled security operations and the speed AI brings are also critical for defending their organization’s growing AI deployments and the expanded attack surface those deployments create.
“AI is a big bang for the attack surface. The models are expanding the surface so quickly,” says Deloitte’s U.S. cyber AI leader Mark Nicholson.
Nicholson says the growing use of AI doesn’t change the fundamental responsibilities of the security program, “but it does change the urgency and the way security needs to be implemented. CISOs now see embedding cybersecurity and trust and transparency in the AI development process as a priority. CISOs must have as a priority secure AI and trust in AI by design.”
Reining in shadow AI
CISOs acknowledge they must also confront the risks that unsanctioned AI deployments create.
“When you look at risks of shadow AI, you’re looking at loss of control of data, an expanded attack surface, compliance and regulatory risk, lack of control and visibility, loss of intellectual property, and reputational damage,” says Lina Dabit, executive director of the CISO office at Optiv Canada. “And there is also the risk of inaccurate and biased outcomes, because if you’re employees aren’t using AI through a sanctioned process, then the question also becomes where are they getting their information from [to feed to the shadow AI system] and how reliable is it.”
CISOs are monitoring their environments for shadow AI and educating the workforce on its risks, Dabit says, but many continue to encounter uses of unsanctioned AI in their organizations.
Some research predicts the security risks of shadow AI will be an even bigger issue in the coming year. Researchers for Google Cloud Security’s Cybersecurity Forecast 2026 report write that “by 2026, we expect the proliferation of sophisticated AI Agents will escalate the ‘Shadow AI’ problem into a critical ‘Shadow Agent’ challenge. In organizations, employees will independently deploy these powerful, autonomous agents for work tasks, regardless of corporate approval. This will create invisible, uncontrolled pipelines for sensitive data, potentially leading to data leaks, compliance violations, and IP theft.”
Google researchers say that “banning agents is not a viable option, as it only drives usage off the corporate network, eliminating visibility.” Instead, they advise “a new discipline of AI security and governance” and, like Nicholson, advocate for “a secure-by design approach, integrating protection from the start.”
Rethinking identity and access management
The growing use of AI has CISOs in 2026 prioritizing another longstanding area of security work: identity and access management. This came in No. 6 on Foundry’s survey of top CISO priorities for the coming year.’
Jon France, CISO of ISC2, a cybersecurity training and certification organization, says there’s a heightened importance to identity management as organizations start to deploy agentic AI — a move that will require organizations to manage “not just human identities but thing identities as well.”
France is using zero trust and multifactor authentication to help ensure only authorized entities — whether humans or machines — gain access to systems. He’s also evaluating the use of passkeys instead of tokens for authentication.
Still, he recognizes that he and others have a big challenge around identity and access management as agents become more common and where the proliferation of agents introduces more potential for some agents to gain unauthorized permissions to access systems from other agents in the chain.
Defending against deepfakes
Mike Baker, CISO at DXC Technology, is also prioritizing identity — but he’s specifically concerned with verifying the identity of people in an era of deepfakes.
“We want to make sure the person you’re talking to or emailing is really the person you think it is,” he says, noting that AI advancements enable hackers to make a deepfake that is nearly indistinguishable from the real McCoy.
Baker says he’s using various security tools (including multimodal authentication) and strategies (such as employee training) to counteract the deepfake threat and help ensure his organization’s employees can spot a deepfake scam.
Tackling third-party management
Baker also lists improving third-party risk management as a priority. It’s one shared by many CISOs, coming in at No. 11 on Foundry’s survey.
Third-party risk has always been there, France says, but it’s coming to the fore as organizations have an increasing number of suppliers and an increasing reliance on them to operate. Major outages at AWS, Azure, and Cloudflare in 2025 should indicate to all organizations the importance of strengthening third-party risk management, he says.
Baker adds that AI also fuels the need to improve third-party risk management practices. As a CISO, he wants to understand the AI models built into the software products his organization is using to ensure they’re protecting his company’s data, that their models are secure, and that they’re reliable.
Bolstering resiliency
France says third-party risk management can also bolster corporate resiliency — another priority for him and other CISOs. It came in at No. 13 on Foundry’s CISO priorities list.
Research firm Gartner lists resiliency as one of three key themes for CISOs in 2026, noting that “cyber resilience goes well beyond IT recovery plans — it includes legal, public relations, market disclosures, and supplier readiness. It’s about full, end-to-end coordination and readiness across departments.”
Aaron McCray, field CISO for technology solutions and services company CDW, says more CISOs are focused on resiliency as security leaders work to align with business strategy and see security as a business enabler.
“CISOs are looking at how they can recover from operational events, not just cyber events, they’re looking at how to retain functions during crises and how to restore functions in real-time,” McCray adds.
Grappling with geopolitical risk
CISOs in 2026 are paying more attention to geopolitical risks, says Betsy Soehren Jones, a partner at technology consulting firm West Monroe.
There is good reason for the heightened interest in international affairs, as global events can spur those nation-states already engaged in cyberattacks to ramp up their activities, Soehren Jones explains. Global events can also disrupt supply chains and resources, including offshore workers and software services, she adds, which can have implications for CISOs and their teams.
Soehren Jones, who formerly worked as director of security strategy at an energy company, advises CISOs to join intelligence communities, such as industry ISACs, as well as to review White House executive orders, federal directives, and similar material to glean information on emerging geopolitical risks and threats.
She also advises CISOs to work with their company’s federal affairs office, if their company has one, to better understand and prepare for the global issues that concern the company. CISOs should also work with trade associations and follow the US Chamber of Commerce to stay abreast of geopolitical risks, she adds.
PwC’s 2026 Global Digital Trust Insights found that 60% of the 3,887 business and tech executives across 72 countries surveyed for the study ranked cyber risk investment in their top three strategic priorities in response to ongoing geopolitical uncertainty.
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CSOonline

SBOM erklärt: Was ist eine Software Bill of Materials?

Softwareentwicklung und Autoproduktion haben mehr gemein, als man denkt. Lesen Sie, was Sie zum Thema Software Bill of Materials (SBOM) wissen sollten.
Foto: Ju1978 – shutterstock.com
Eine Software Bill of Materials ist ein detaillierter Leitfaden, der unter anderem Aufschluss über die Komponenten Ihrer Software gibt. Als eine Art Stückliste hilft eine SBOM Anbietern und Käufern gleichermaßen, den Überblick über die Komponenten zu behalten und die Sicherheit der Softwarelieferkette zu verbessern.
SBOM – Definition
Eine Software Bill of Materials ist eine formale, strukturierte Aufzeichnung, die die
Komponenten eines Softwareprodukts und
ihre Beziehungen innerhalb der Softwarelieferkette
beschreibt. Eine SBOM gibt also einerseits an, welche Pakete und Bibliotheken in Ihre Anwendung eingeflossen sind, andererseits auch die Beziehung zwischen diesen Paketen und Bibliotheken und anderen vorgelagerten Projekten. Das ist besonders wichtig ist, wenn es um wiederverwendeten Code und Open-Source-Komponenten geht.
Sie kennen Stücklisten vielleicht im Zusammenhang mit Neuwagen. In diesem Fall handelt es sich um ein Dokument, das jede Komponente, die sich in Ihrem neuen Fahrzeug befindet, detailliert beschreibt. Auch wenn Ihr Auto von Toyota oder General Motors zusammengebaut wurde: Viele seiner Komponenten stammen von Subunternehmern auf der ganzen Welt. Die Stückliste gibt Aufschluss darüber, woher jedes einzelne dieser Teile stammt. Das dient nicht nur der Transparenz, sondern auch der Sicherheit: Wird eine bestimmte Serie von Airbags zurückgerufen, müssen die Fahrzeughersteller schnell herausfinden können, wo diese verbaut sind.
Da Open-Source-Bibliotheken von Drittanbietern sich jedoch zunehmender Beliebtheit erfreuen, um containerisierte, verteilte Applikationen zu erstellen, weisen Softwareentwicklung und Fahrzeugfertigung inzwischen mehr Gemeinsamkeiten auf, als man denkt. Sowohl Entwickler als auch Benutzer können eine Software Bill of Materials verwenden, um nachzuvollziehen, welche Bestandteile in die Software eingeflossen sind, wie sie verteilt und verwendet wurden. Das erlaubt – insbesondere aus Sicherheitsperspektive – eine Reihe wichtiger Rückschlüsse.
Software Bill of Materials – Vorteile
Die Zeiten monolithischer, proprietärer Codebasen sind längst vorbei. Moderne Anwendungen basieren oft auf in großen Teilen wiederverwendetem Code – häufig mit Beteiligung von Open-Source-Bibliotheken. Diese Anwendungen werden auch zunehmend in kleinere, in sich geschlossene Funktionskomponenten, so genannte Container, aufgeteilt, die über Orchestrierungsplattformen wie Kubernetes gemanagt und lokal oder in der Cloud ausgeführt werden.
Im Großen und Ganzen waren diese Veränderungen ein Segen für die Softwareentwicklung und haben dazu beigetragen, die Entwicklerproduktivität zu erhöhen und Kosten zu senken. Aus Security-Perspektive sieht das Bild nicht ganz so rosig aus: Indem sie sich in hohem Maße auf den Code von Drittanbietern verlassen, (deren interne Prozesse sie möglicherweise nicht oder nur teilweise kennen), haben Entwickler eine Lieferkette von Softwarekomponenten geschaffen, die genauso komplex ist, wie die von Herstellern physischer Produkte. Da eine Anwendung jedoch nur so sicher ist wie ihre schwächste Komponente, kann dieses Gebahren gravierende Schwachstellen zur Folge haben. Die 2020er Jahre waren von einer Reihe von Angriffen auf die Softwarelieferkette geprägt, die für Schlagzeilen sorgten:
Ende 2020 gelang es Hackern, die mit dem russischen Geheimdienst in Verbindung stehen sollen, eine Backdoor in die Netzwerk-Monitoring-Plattform von SolarWinds einzuschleusen. Diese wird wiederum von anderen Sicherheitsprodukten genutzt, was zu ihrer Kompromittierung führte.
Ende 2021 wurde eine schwerwiegende Sicherheitslücke in Apache Log4j entdeckt, einer Java-Bibliothek, die für die Protokollierung von Systemereignissen verwendet wird. Das hört sich nur so lange langweilig an, bis man feststellt, dass fast jede Java-Anwendung Log4j in irgendeiner Form verwendet und damit angreifbar wird.
Diese Sicherheitskrisen verdeutlichen die potenzielle Rolle der Software Bill of Materials innerhalb der Sicherheitslandschaft. Viele Anwender haben vielleicht nur beiläufig von diesen Schwachstellen gehört, waren sich aber nicht bewusst, dass sie Log4j oder eine andere SolarWinds-Komponente verwenden. Mit einer SBOM wissen Sie genau, welche Pakete Sie installiert haben – und vor allem, welche Versionen dieser Pakete. So können Sie bei Bedarf aktualisieren, um auf der sicheren Seite zu sein.
Eine Software Bill of Material kann auch über die Sicherheit hinausgehen: SBOMs können Entwicklern beispielsweise dabei helfen, den Überblick über die Open-Source-Lizenzen ihrer verschiedenen Softwarekomponenten zu behalten, was wichtig ist, wenn es darum geht, Applikationen zu distribuieren.
SBOMs – Pflicht in den USA und bald auch in Europa
Der SolarWinds-Hack hat insbesondere bei der US-Regierung die Alarmglocken schrillen lassen – auch weil viele US-Bundesbehörden die kompromittierte Komponente eingesetzt hatten. Deshalb enthielt die im Mai 2022 von der Biden-Regierung erlassene Cybersecurity-Verordnung auch Richtlinien im Zusammenhang mit Software Bill of Materials. Das US-Handelsministerium veröffentlichte einen Leitfaden, welche grundlegenden Elemente in SBOMs enthalten sein müssen.
Obwohl sich die Anordnung speziell auf diejenigen bezieht, die in direkter Beziehung zu den US-Bundesbehörden stehen, werden die Regelungen weitergehende Auswirkungen haben. Schließlich werden die an die US-Regierung verkauften Produkte, die nun mit einer SBOM ausgeliefert werden müssen, größtenteils auch an andere Unternehmen und Organisationen verkauft. Viele Softwarehersteller hoffen, dass die Kunden aus der Privatwirtschaft SBOMs ebenfalls als Mehrwert betrachten.
Außerdem ist das staatliche Auftragswesen selbst eine Lieferkette, wie Sounil Yu, ehemaliger Chief Security Scientist bei der Bank of America und jetzt CISO und Forschungsleiter bei JupiterOn, unterstreicht: “Es gibt nur eine bestimmte Anzahl von Unternehmen, die direkt mit der US-Regierung zusammenarbeiten und von der Verordnung betroffen sind. Die Auswirkungen auf der zweiten Zuliefererebene sind noch wesentlich größer.”
In Europa wird die SBOM ebenfalls verpflichtend – und zwar im Rahmen der Umsetzung des Cyber Resilience Act bis Ende 2027.
Software Bill of Materials – Aufbau
Als Reaktion auf die Executive Order veröffentlichte die National Telecommunications and Information Administration (NTIA) im Juli 2021 den Leitfaden “The Minimum Elements For a Software Bill of Materials” (PDF). Das Dokument könnte zu einem De-facto-Standard für SBOMs in der gesamten Branche werden und legt sieben Datenfelder fest, die jede SBOM enthalten sollte:
Name des Anbieters: Der Name einer Einheit, die eine Komponente erstellt, definiert und identifiziert.
Komponentenname: Die Bezeichnung, die einer vom ursprünglichen Lieferanten definierten Softwareeinheit zugewiesen wird.
Version der Komponente: Eine Kennung, die vom Lieferanten verwendet wird, um eine Änderung der Software gegenüber einer zuvor identifizierten Version anzugeben.
Andere eindeutige Identifikatoren: Andere Informationen, die verwendet werden, um eine Komponente zu identifizieren oder als Nachschlageschlüssel für relevante Datenbanken dienen. Das könnte etwa ein Identifikator aus dem NIST CPE Dictionary sein.
Abhängigkeitsbeziehung: Kennzeichnet die Beziehung, in der eine Upstream-Komponente X in Software Y enthalten ist. Das ist besonders wichtig für Open-Source-Projekte.
Autor der SBOM-Daten: Der Name der Entität, die die SBOM-Daten erstellt.
Zeitstempel: Aufzeichnung des Datums und der Uhrzeit der Zusammenstellung der SBOM-Daten.
SBOMs müssen darüber hinaus auch folgende Anforderungen erfüllen:
Die SBOM muss in einem von drei standardisierten Formaten vorliegen, damit sie maschinenlesbar ist – SPDX, CycloneDX oder SWID-Tags.
Mit jeder neuen Softwareversion muss eine neue SBOM generiert werden, um sicherzustellen, dass sie auf dem neuesten Stand ist.
Die SBOM muss nicht nur Abhängigkeitsbeziehungen enthalten, sondern auch Aufschluss darüber geben, wo solche Beziehungen wahrscheinlich bestehen, aber der Organisation, die die SBOM erstellt, unbekannt sind.
SBOM erstellen – so geht’s
Wenn Sie diesen Artikel lesen, empfinden Sie es möglicherweise als entmutigende Aufgabe, eine Software Bill of Materials zu erstellen. Schließlich muss es ein Alptraum sein, all diese Informationen manuell zusammenzutragen. Glücklicherweise werden SBOMs in den meisten Fällen mit Hilfe von SCA-Tools (Software Composition Analysis ) automatisch erstellt. Diese Tools werden häufig in DevSecOps-Pipelines eingesetzt und spielen nicht nur für die Erstellung von SBOMs eine Rolle.
SCA-Tools durchsuchen Ihre Codeverzeichnisse nach Paketen und vergleichen sie mit Online-Datenbanken, um sie mit bekannten Bibliotheken abzugleichen. Es gibt aber auch Werkzeuge, die eine Software Bill of Materials im Rahmen des Software-Build-Prozesses erstellen. Die OWASP Foundation hat eine umfassende Liste von SCA-Tools zusammengestellt, die von einfachen, quelloffenen Kommandozeilen-Tools bis hin zu spezialisierten, kommerziellen Produkten reicht. Wenn Sie tiefer in diesen Bereich eintauchen möchten, sollten Sie außerdem einen Blick auf unseren Artikel “7 Tools, die Ihre Softwarelieferkette absichern” werfen.
Wenn Sie verteilte Software entwickeln, wird es immer wichtiger, SBOMs in Ihre Entwicklungspraxis zu integrieren. Auch wenn Sie keine Verträge mit der US-Regierung abschließen – Sie sollten sich angesichts der Bedrohungslage in jedem Fall Gedanken über die Sicherheit ihrer Softwarelieferkette machen.
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Apple Watch Series 11 on Sale for Record Low Price of $299 ($100 Off)

Amazon and Best Buy this weekend have all-time low prices on the Apple Watch Series 11, with $100 discounts across numerous models of the smartwatch.

Note: MacRumors is an affiliate partner with Amazon. When you click a link and make a purchase, we may receive a small payment, which helps us keep the site running.

You can get the 42mm GPS Apple Watch Series 11 for $299.00, down from $399.00, and the 46mm GPS model for $329.00, down from $429.00. On Amazon, you'll find four of the 42mm GPS models on sale at this all-time low price, and three of the 46mm GPS models on sale.

$100 OFFApple Watch Series 11 (42mm GPS) for $299.00
$100 OFFApple Watch Series 11 (46mm GPS) for $329.00

If you're shopping for cellular models, you can find record low prices on multiple models this week on Amazon. The 42mm cellular Apple Watch Series 11 has hit $399.00, down from $499.00, and the 46mm cellular model has hit $429.00, down from $529.00.

$100 OFFApple Watch Series 11 (42mm Cell) for $399.00
$100 OFFApple Watch Series 11 (46mm Cell) for $429.00

Head to our full Deals Roundup to get caught up with all of the latest deals and discounts that we've been tracking over the past week.



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Top Stories: CES 2026 Highlights, Apple Card Moving to Chase, and More

Even without any announcements from Apple, CES dominated tech news this week with a host of upcoming products and technologies being demonstrated at the annual expo in Las Vegas.


Other news in the Apple world this week included official word that the Apple Card will shift from Goldman Sachs to Chase, while iOS 26 appears to be showing extremely slow adoption rates amid the controversial Liquid Glass redesign, so read on below for all the details on these stories and more!

Top Stories

CES 2026 Hub: Highlights From the Show

The annual consumer electronics show CES was once again held this week in Las Vegas. AI and robots were some of the high-profile areas of focus this year, and even though Apple itself doesn't officially attend the show, we still saw a variety of more traditional products that are always popular with Apple fans.


One of the products shown at the show that appears to be more directly relevant to Apple came from Samsung, which briefly showed off its new crease-less foldable OLED display panel. The panel is rumored to be destined for Apple's upcoming foldable iPhone expected to debut later this year.

Another item at CES that has proven popular is the Clicks Communicator, a new Android smartphone intended to be carried as a second phone for focus on communication rather than consumption, with Clicks calling it akin to a Kindle's relationship to the iPad.

Check out our CES 2026 news hub, and head over to our YouTube channel for our daily videos from the show floor.

Apple Card Will Move From Goldman Sachs to JPMorgan Chase

After over two years of rumors, the move is now official: Goldman Sachs is giving up the Apple Card business with JPMorgan Chase to become the new partner for Apple's credit card and savings account business.


The transition will take around two years to play out, and in the meantime Apple Card customers can continue using their cards as usual.

iOS 26 Shows Unusually Slow Adoption Months After Release

iOS 26 is showing unusually slow adoption among iPhone users months after release, according to third-party analytics.


Usage data published by StatCounter for January 2026 indicates that only around 15 to 16% of active iPhones worldwide are running any version of ‌iOS 26‌. Historical comparisons highlight how atypical this adoption curve appears. StatCounter data from January 2025 shows that roughly 63% of iPhones were running some version of iOS 18 about four months after its release. In January 2024, iOS 17 had reached approximately 54% adoption over a similar timeframe, while iOS 16 surpassed 60% adoption by January 2023.

Logitech Blames 'Inexcusable Mistake' After Certificate Expiry Breaks macOS Apps

Logitech users on macOS found themselves locked out of their mouse customizations this week after the company let a security certificate expire, breaking both its Logi Options+ and G HUB configuration apps.


Logitech devices like the MX Master series mice and MX Keys keyboards stopped working properly as a result of the oversight, with users unable to access their custom scrolling setup, button mappings, and gestures. It wasn't long before the Logitech subreddit was awash with frustrated reports as people discovered their configured peripherals had suddenly reverted to default settings.

Logitech quickly issued updates to address the issue, but they require a manual update as the problem left the auto-updating feature unusable since the apps were unable to open.

OpenAI Launches ChatGPT Health With Apple Health Integration

OpenAI this week announced the launch of ChatGPT Health, a dedicated section of ChatGPT where users can ask health-related questions completely separated from their main ChatGPT experience.


For more personalized responses, users can connect various health data services such as Apple Health, Function, MyFitnessPal, Weight Watchers, AllTrails, Instacart, and Peloton. Once connected to Apple Health, ChatGPT will be able to access your health and fitness data, including movement, sleep, and activity patterns.

Low-Price 12.9-Inch MacBook With A18 Pro Chip Reportedly Launching Early This Year

Apple plans to introduce a 12.9-inch MacBook in spring 2026, according to TrendForce. The Taiwanese research firm says this MacBook will be aimed at the entry-level to mid-range market, with "competitive pricing."


TrendForce did not share any further details about this MacBook, but the information that it shared lines up with several rumors about a more affordable MacBook, which is expected to be equipped with a version of the iPhone 16 Pro's A18 Pro chip. Apple is expected to release the laptop by March or April of this year.

For more on this budget MacBook, check out our recap of everything we've heard about it so far.

MacRumors Newsletter

Each week, we publish an email newsletter like this highlighting the top Apple stories, making it a great way to get a bite-sized recap of the week hitting all of the major topics we've covered and tying together related stories for a big-picture view.

So if you want to have top stories like the above recap delivered to your email inbox each week, subscribe to our newsletter!Tag: Top Stories
This article, "Top Stories: CES 2026 Highlights, Apple Card Moving to Chase, and More" first appeared on MacRumors.com

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Apple's MacBook Pro Turns 20 Years Old

Today marks the 20th anniversary of the introduction of the MacBook Pro, unveiled by Steve Jobs as a "One More Thing" segment at the end of his Macworld San Francisco keynote on January 10, 2006.


The MacBook Pro was an evolution of the previous PowerBook as the professional-level laptop in Apple's lineup, but with the shift from PowerPC chips to Intel Core chips, Apple decided to launch a rebrand. The ‌MacBook Pro‌ was initially available only in a 15-inch size, with a 17-inch model following a few months later. A 13-inch aluminum MacBook debuted in October 2008, and after just one generation it was folded into the ‌MacBook Pro‌ lineup in 2009.

The original ‌‌MacBook Pro‌‌ came in two configurations, both with 15.4-inch widescreen displays at a resolution of 1,440 × 900 pixels. As announced, the entry-level model priced at $1,999 featured a 1.67GHz Core Duo processor, 512MB of 667MHz DDR2 RAM, and an 80GB hard drive, while the higher-end model priced at $2,499 offered a faster 1.83GHz Core Duo processor, 1GB of RAM, and a 100GB hard drive.

By the time the ‌MacBook Pro‌ started shipping a month later, however, Apple had already upgraded the available Core Duo chips to 1.83GHz in the base model and 2.0GHz in the high-end configuration, while also introducing an even higher-end 2.16GHz build-to-order option.

With its lengthy 20-year history, the ‌MacBook Pro‌ has gone through a lot of changes over its lifetime, adopting key features like a built-in webcam, MagSafe power connector, aluminum unibody construction, high-resolution Retina displays, and more.

Other features were not so well received, including the revolutionary Touch Bar in place of traditional function keys and the butterfly-mechanism keyboard that proved prone to failures and resulted in an extended repair program and multiple class action lawsuits.

In 2020, the 13-inch ‌MacBook Pro‌ was one of three Apple products, alongside the MacBook Air and the Mac mini, to receive the M1 chip, marking a generational shift for Apple away from Intel processors and into its own custom Apple silicon. The move freed Apple up from having to follow the cadence of Intel chip releases, and it allowed Apple to further tighten the integration between hardware and software, leading to significant leaps in performance and efficiency.

Looking toward the future, the next big revolution for the ‌MacBook Pro‌ appears to be coming fairly soon, with rumors indicating we should see a major redesign for the higher-end models with OLED displays, touchscreen support, and perhaps an iPhone-like Dynamic Island cutout in the display in either late 2026 or early 2027. Apple is said to also be planning for thinner and lighter designs, making Apple's most powerful laptops even more portable.Related Roundup: MacBook Pro
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SRE Skills and SLOs: A Comprehensive Guide

Introduction: Problem, Context & Outcome
Modern digital businesses depend on software systems that must remain available, responsive, and resilient at all times. These systems often operate across cloud platforms, microservices, containers, and automated CI/CD pipelines. Engineering teams regularly deal with service outages, slow recovery, alert fatigue, and growing friction between development and operations. As delivery speed increases, reliability often becomes reactive rather than engineered, resulting in downtime, lost revenue, and reduced customer confidence.
The SRE Certified Professional approach directly addresses these problems by treating reliability as an engineering responsibility rather than an operational afterthought. It introduces measurable objectives, automation-driven workflows, and disciplined incident management practices. In a world where users expect uninterrupted digital services, reliability defines success.
This blog provides a comprehensive, practical rewrite explaining the SRE Certified Professional framework, its role in modern DevOps, and how it helps professionals manage real production systems effectively. Why this matters: reliability issues impact customers instantly and damage long-term business trust.
What Is SRE Certified Professional?
The SRE Certified Professional is an industry-aligned certification that validates hands-on Site Reliability Engineering knowledge required to design, operate, and scale modern production systems. It applies software engineering principles to operational challenges, ensuring systems remain reliable while continuing to evolve rapidly.
In DevOps and cloud-native environments, the SRE Certified Professional serves as a structured reliability framework. Instead of aiming for zero failures, it defines acceptable reliability targets and engineers systems to meet them using automation, monitoring, and data-driven decisions. Core practices include Service Level Indicators (SLIs), Service Level Objectives (SLOs), error budgets, observability, and structured incident response.
This certification is especially relevant for distributed systems, Kubernetes platforms, and microservices architectures where manual operations fail to scale. Why this matters: SRE-certified professionals bring predictability and stability to complex environments.
Why SRE Certified Professional Is Important in Modern DevOps & Software Delivery
DevOps focuses on fast software delivery, but speed without reliability leads to fragile systems. The SRE Certified Professional complements Agile, CI/CD, and cloud-native practices by introducing reliability engineering as a first-class concern. Many organizations adopt SRE to maintain service stability while releasing features continuously.
The certification addresses common DevOps challenges such as excessive alerts, unclear service ownership, frequent rollbacks, and unpredictable production behavior. By defining clear reliability targets, teams can make informed decisions about deployments, risk tolerance, and technical debt. Error budgets guide CI/CD velocity instead of subjective judgment.
As organizations increasingly rely on distributed cloud systems, failures become unavoidable but manageable when engineered correctly. Why this matters: long-term DevOps success depends on balancing rapid delivery with dependable services.
Core Concepts & Key Components
Service Level Indicators (SLIs)
Purpose: Measure real service performance from the user’s point of view.
How it works: Teams track metrics such as latency, error rates, throughput, and availability using monitoring data.
Where it is used: Production services, APIs, platforms, and customer-facing applications.
Service Level Objectives (SLOs)
Purpose: Define target reliability levels aligned with business needs.
How it works: Teams agree on measurable objectives like 99.9% availability over a defined period.
Where it is used: Release planning, operational reviews, and cross-team alignment.
Error Budgets
Purpose: Balance innovation speed with system stability.
How it works: Teams accelerate releases when budgets are healthy and focus on reliability when budgets are consumed.
Where it is used: CI/CD pipelines and change management processes.
Monitoring and Observability
Purpose: Provide deep visibility into system health and behavior.
How it works: Metrics, logs, and traces reveal performance issues and root causes.
Where it is used: Incident detection, analysis, and performance optimization.
Incident Management
Purpose: Reduce outage impact and recovery time.
How it works: On-call rotations, runbooks, escalation paths, and blameless postmortems guide responses.
Where it is used: Live production incidents and post-incident analysis.
Automation and Toil Reduction
Purpose: Eliminate repetitive, manual operational work.
How it works: Pipelines, scripts, and self-healing systems replace human intervention.
Where it is used: Deployments, scaling, backups, and disaster recovery.
Why this matters: these components create a repeatable foundation for reliable and scalable system operations.
How SRE Certified Professional Works (Step-by-Step Workflow)
The SRE workflow begins by defining reliability in user-centric terms. Teams identify SLIs that reflect customer experience and set SLOs aligned with business priorities. These objectives guide engineering decisions across development and operations.
Monitoring tools continuously track performance against SLOs. Alerts activate only when user impact occurs, significantly reducing alert noise. Engineers respond using standardized incident workflows supported by automation.
Following incidents, teams conduct blameless postmortems to identify causes and preventative improvements. Over time, automation replaces manual fixes, and error budgets shape future release strategies.
This workflow integrates naturally into DevOps without slowing delivery. Why this matters: disciplined reliability management enables continuous delivery without operational chaos.
Real-World Use Cases & Scenarios
In SaaS companies, SRE Certified Professionals maintain service availability during rapid feature releases. They collaborate with developers to design resilient services and monitor user-facing reliability metrics.
In e-commerce platforms, SREs prepare for high-traffic events by improving observability, capacity planning, and automated scaling. QA teams rely on SRE metrics to validate production readiness.
In enterprise cloud environments, SREs work with DevOps and cloud teams to manage Kubernetes clusters, automate recovery, and reduce operational risk. Business stakeholders benefit from predictable performance and fewer incidents.
Why this matters: real-world SRE practices directly influence customer satisfaction and revenue protection.
Benefits of Using SRE Certified Professional
Productivity: Less firefighting and more focus on delivering value. Reliability: Measurable targets improve system consistency. Scalability: Automation supports growth without operational overload. Collaboration: Shared reliability goals align DevOps, development, and operations teams. Why this matters: these benefits translate technical improvements into business outcomes.
Challenges, Risks & Common Mistakes
Many organizations treat SRE as a tooling exercise instead of a mindset change. Unrealistic SLOs create unnecessary pressure and burnout. Over-alerting causes teams to miss critical incidents. Poorly tested automation introduces new failures.
Effective mitigation includes starting small, focusing on user impact, reviewing objectives regularly, and validating automation carefully before expanding.
Why this matters: understanding common pitfalls ensures long-term, sustainable SRE adoption.
Comparison Table
DimensionTraditional OperationsDevOpsSRE Certified ProfessionalOperating styleReactiveSpeed-focusedReliability engineeringAutomationLowMediumHighMetricsInfrastructure-basedPipeline metricsUser-centric SLIsRelease modelRisk-averseFrequentError-budget drivenIncident handlingAd hocFaster responseStructured and measuredTeam cultureSiloedCollaborativeBlamelessScalingManualElasticPredictiveLearningLimitedIterativeContinuous improvementRisk managementSubjectiveBasicQuantifiedBusiness impactUnclearFaster releasesTrust and continuity Why this matters: comparison demonstrates why SRE delivers a mature reliability model.
Best Practices & Expert Recommendations
Start with a small set of SLIs tied directly to user experience. Review and refine SLOs quarterly as business needs evolve. Automate repetitive operational work early to reduce toil. Invest in observability before scaling aggressively.
Promote blameless postmortems to encourage learning and improvement. Introduce SRE practices gradually into DevOps workflows to ensure adoption and cultural alignment.
Why this matters: best practices ensure reliability improvements remain effective over time.
Who Should Learn or Use SRE Certified Professional?
The SRE Certified Professional certification is ideal for Developers, DevOps Engineers, Cloud Engineers, SREs, QA professionals, and technical leaders responsible for production systems. Beginners gain structured foundations, while experienced engineers formalize advanced reliability skills.
Teams working with cloud platforms, microservices, and CI/CD pipelines benefit the most.
Why this matters: targeting the right audience maximizes career growth and organizational value.
FAQs – People Also Ask
What is SRE Certified Professional?
It validates applied Site Reliability Engineering skills. Why this matters: shows production readiness.
Why is it used?
To balance speed with reliability. Why this matters: unstable systems lose trust.
Is it suitable for beginners?
Yes, with basic DevOps knowledge. Why this matters: structured learning prevents errors.
How is it different from DevOps certification?
It focuses deeply on reliability engineering. Why this matters: reliability gaps are expensive.
Is it relevant for cloud roles?
Yes, especially cloud-native systems. Why this matters: cloud failures scale rapidly.
Does it require coding?
Basic scripting is helpful. Why this matters: accessible across roles.
Which tools are covered?
Monitoring, automation, and CI/CD tools. Why this matters: tool-agnostic knowledge lasts longer.
How long is it relevant?
Several years due to core principles. Why this matters: strong ROI.
Can QA professionals use it?
Yes, for production readiness insights. Why this matters: quality extends beyond testing.
Does it improve career growth?
Yes, SRE skills are highly valued. Why this matters: reliability expertise is in demand.
Branding & Authority
DevOpsSchool is a globally trusted training platform offering enterprise-ready programs in DevOps, cloud computing, and automation. Its focus on real production challenges and hands-on learning helps professionals develop job-ready skills aligned with modern industry requirements.
Why this matters: credible platforms ensure career-safe, industry-relevant learning.
Rajesh Kumar brings over 20 years of hands-on experience across DevOps, DevSecOps, Site Reliability Engineering, DataOps, AIOps, MLOps, Kubernetes, cloud platforms, CI/CD, and automation. His mentoring emphasizes practical execution and operational excellence.
Why this matters: experienced guidance accelerates real-world skill development.
The SRE Certified Professional program validates applied SRE skills for modern DevOps and cloud-native environments by combining reliability engineering with automation and continuous delivery.
Why this matters: industry-aligned certification proves operational competence.
Call to Action & Contact Information
Advance your DevOps and cloud career by mastering reliability engineering through the SRE Certified Professional program.
Email: [email protected]
Phone & WhatsApp (India): +91 7004215841
Phone & WhatsApp (USA): +1 (469) 756-6329



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SRE Monitoring and Observability: A Comprehensive Guide

Introduction: Problem, Context & Outcome
Digital applications today support critical business workflows, and even brief downtime can disrupt revenue and customer confidence. Engineering teams now deploy code rapidly, but many still rely on reactive operational practices that struggle under cloud-native and microservices complexity. As systems grow distributed, failures become harder to predict and resolve quickly. Reliability can no longer depend on manual firefighting or individual expertise. Organizations need a disciplined engineering approach that embeds reliability into everyday development and operations. The Site Reliability Engineering (SRE) Training provides this approach by combining software engineering principles with operational rigor. Readers gain practical understanding of how to manage system health, reduce outages, and operate services predictably in real production environments.
Why this matters: Strong reliability practices protect business continuity, user trust, and long-term scalability.
What Is Site Reliability Engineering (SRE) Training?
Site Reliability Engineering (SRE) Training teaches professionals how to build, operate, and scale reliable systems using engineering-driven methods. SRE applies software development techniques to operational challenges, focusing on automation, measurement, and continuous improvement. Instead of reacting to incidents, teams define reliability goals and design systems to meet them consistently. Developers, DevOps engineers, and SRE teams use these practices to manage uptime, latency, and capacity. The training introduces core ideas such as service level indicators, service level objectives, error budgets, monitoring, and incident management. In production environments, SRE creates a shared reliability language across teams. This training prepares professionals to manage complex systems with confidence and clarity.
Why this matters: A common reliability framework replaces guesswork with measurable engineering discipline.
Why Site Reliability Engineering (SRE) Training Is Important in Modern DevOps & Software Delivery
Modern DevOps emphasizes speed, automation, and frequent releases, but speed without reliability increases operational risk. SRE introduces guardrails that allow teams to move fast while staying in control. Organizations adopt SRE to operate cloud platforms, microservices, and large-scale distributed systems. SRE addresses issues such as alert fatigue, repeated outages, and slow incident recovery. It integrates naturally with CI/CD pipelines, cloud services, Agile workflows, and DevOps automation tools. Site Reliability Engineering (SRE) Training helps teams align delivery velocity with measurable reliability outcomes.
Why this matters: Sustainable software delivery depends on reliability growing alongside innovation.
Core Concepts & Key Components
Service Level Indicators (SLIs)
Purpose: Measure how a service performs in production.
How it works: SLIs track latency, error rates, and availability.
Where it is used: Monitoring dashboards.
Service Level Objectives (SLOs)
Purpose: Define acceptable reliability levels.
How it works: SLOs set targets based on SLIs.
Where it is used: Reliability planning.
Error Budgets
Purpose: Balance change and stability.
How it works: Error budgets define allowable failure.
Where it is used: Release decisions.
Monitoring and Observability
Purpose: Understand system behavior.
How it works: Metrics, logs, and traces provide visibility.
Where it is used: Incident detection.
Incident Management
Purpose: Restore service efficiently.
How it works: Structured response processes guide recovery.
Where it is used: Production incidents.
Toil Reduction
Purpose: Reduce repetitive manual work.
How it works: Automation replaces routine tasks.
Where it is used: Daily operations.
Capacity Planning
Purpose: Prepare for growth.
How it works: Forecasting aligns resources with demand.
Where it is used: Scaling strategies.
Change Management
Purpose: Limit deployment risk.
How it works: Controlled rollouts reduce impact.
Where it is used: CI/CD pipelines.
Reliability Automation
Purpose: Enforce consistency.
How it works: Tools automate reliability checks.
Where it is used: Platform operations.
Post-Incident Reviews
Purpose: Prevent recurrence.
How it works: Blameless reviews identify improvements.
Where it is used: Continuous improvement.
Why this matters: These components together form a repeatable reliability operating model.
How Site Reliability Engineering (SRE) Training Works (Step-by-Step Workflow)
SRE starts by defining service reliability goals through SLOs. Teams monitor system behavior using SLIs and compare results against those objectives. Error budgets guide decisions around release frequency and acceptable risk. Monitoring systems provide early signals of degradation. When incidents occur, teams follow structured response processes to restore service quickly. After recovery, blameless reviews identify root causes and automation opportunities. This workflow integrates directly with DevOps lifecycles and CI/CD pipelines.
Why this matters: A defined workflow converts reliability from reaction into continuous improvement.
Real-World Use Cases & Scenarios
Streaming platforms rely on SRE to remain available during traffic spikes and live events. Financial services use SRE to meet strict uptime and compliance requirements. DevOps teams collaborate with SREs to deploy safely. Developers design services with reliability metrics in mind. QA teams validate performance thresholds. Cloud engineers scale infrastructure efficiently. Across industries, SRE reduces downtime, shortens recovery times, and improves user experience.
Why this matters: Real-world usage shows SRE delivers measurable business value.
Benefits of Using Site Reliability Engineering (SRE) Training
Productivity: Less firefighting and manual intervention Reliability: Predictable availability and performance Scalability: Growth without instability Collaboration: Shared ownership across engineering teams Why this matters: Trained teams operate production systems with confidence and efficiency.
Challenges, Risks & Common Mistakes
Teams sometimes treat SRE as traditional operations under a new label. Poorly defined SLOs create confusion. Too many alerts hide critical signals. Manual processes increase burnout. Site Reliability Engineering (SRE) Training addresses these challenges by emphasizing metrics, automation, and disciplined incident handling.
Why this matters: Avoiding these mistakes protects reliability gains and team morale.
Comparison Table
AspectTraditional OperationsSRE ApproachReliability MetricsInformalSLO-drivenIncident ResponseReactiveStructuredAutomationLimitedExtensiveRelease RiskHighManagedOperational ToilHighReducedScalabilityManualPlannedMonitoringBasicObservability-focusedTeam AlignmentSiloedCross-functionalCloud ReadinessLowHighBusiness ImpactUnpredictableMeasured Why this matters: This comparison highlights why organizations move from legacy operations to SRE.
Best Practices & Expert Recommendations
Teams should align SLOs with customer expectations. Automation should replace repetitive tasks wherever possible. Monitoring must focus on user-impacting signals. Incident reviews should remain blameless and action-oriented. Reliability strategies must evolve with system complexity.
Why this matters: Best practices ensure reliability improvements remain effective long term.
Who Should Learn or Use Site Reliability Engineering (SRE) Training?
DevOps engineers managing pipelines benefit from SRE practices. Developers building production services gain reliability awareness. SRE professionals refine operations at scale. QA teams validate performance goals. Cloud engineers manage infrastructure growth. Beginners gain structure, while experienced engineers deepen operational maturity.
Why this matters: Correct audience alignment maximizes learning and business impact.
FAQs – People Also Ask
What is Site Reliability Engineering?
It applies engineering principles to operations.
Why this matters: It defines the SRE philosophy.
Is SRE different from DevOps?
SRE complements DevOps practices.
Why this matters: Collaboration improves outcomes.
Is SRE suitable for beginners?
Yes, with basic system knowledge.
Why this matters: Entry remains accessible.
Does SRE require coding skills?
Yes, automation depends on programming.
Why this matters: Engineering skills are essential.
Is SRE relevant for cloud environments?
Yes, cloud-native systems rely on it.
Why this matters: Cloud adoption continues to grow.
Do startups use SRE?
Yes, to scale safely.
Why this matters: Reliability supports growth.
Does SRE slow deployments?
No, it enables safer speed.
Why this matters: Balance protects innovation.
Is monitoring central to SRE?
Yes, observability guides action.
Why this matters: Visibility prevents failures.
Are error budgets optional?
No, they guide risk decisions.
Why this matters: Measured risk improves stability.
Does SRE improve career prospects?
Yes, global demand remains strong.
Why this matters: Skills stay future-proof.
Branding & Authority
DevOpsSchool is a globally trusted training platform delivering enterprise-grade education in DevOps, cloud computing, automation, and reliability engineering. The platform emphasizes hands-on labs, real production scenarios, and curricula aligned with industry needs. DevOpsSchool enables professionals to build skills that translate directly into reliable systems and enterprise success.
Why this matters: Trusted education leads to real operational capability.
Rajesh Kumar brings over 20 years of hands-on expertise across DevOps & DevSecOps, Site Reliability Engineering (SRE), DataOps, AIOps & MLOps, Kubernetes & Cloud Platforms, and CI/CD & Automation. His mentorship combines deep technical insight with enterprise execution experience, helping learners operate and scale reliable systems with confidence.
Why this matters: Proven leadership strengthens credibility and learning outcomes.
Call to Action & Contact Information
Explore the complete Site Reliability Engineering (SRE) Training and start building reliability-first engineering skills today.
Email: [email protected]
Phone & WhatsApp (India): +91 7004215841
Phone & WhatsApp (USA): +1 (469) 756-6329




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MuddyWater Launches RustyWater RAT via Spear-Phishing Across Middle East Sectors

The Iranian threat actor known as MuddyWater has been attributed to a spear-phishing campaign targeting diplomatic, maritime, financial, and telecom entities in the Middle East with a Rust-based implant codenamed RustyWater. "The campaign uses icon spoofing and malicious Word documents to deliver Rust based implants capable of asynchronous C2, anti-analysis, registry persistence, and modularView the full article
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Selenium with Java Frameworks: A Comprehensive Guide

Introduction: Problem, Context & Outcome
Product teams ship updates rapidly, yet many still face quality risks caused by slow and inconsistent testing. Manual checks struggle to keep pace with frequent UI updates, multiple browsers, and short release cycles. As applications grow, even small regressions can reach users when testing lacks automation and repeatability. Modern delivery demands testing that runs continuously alongside builds. Selenium paired with Java provides a proven approach for automating browser-based validation at scale. The Selenium with Java Training equips professionals to replace brittle manual processes with structured, maintainable automation. Readers learn how to design robust test frameworks, embed tests into CI/CD pipelines, and support rapid delivery while protecting user experience and system stability.
Why this matters: Consistent automation keeps releases fast without sacrificing quality or customer trust.
What Is Selenium with Java Training?
Selenium with Java Training is a structured program focused on automating web application testing using the Selenium framework and Java language. Selenium drives browser interactions, while Java offers stability, scalability, and strong enterprise adoption. QA engineers, developers, and DevOps professionals use this combination to validate UI workflows, catch regressions early, and ensure cross-browser behavior. The training emphasizes real-world practices such as framework architecture, reusable components, reporting, and pipeline integration. Instead of isolated scripts, learners build automation designed for long-term maintenance. The program guides participants from fundamentals to enterprise-ready testing solutions aligned with Agile and DevOps delivery models.
Why this matters: Well-structured automation reduces maintenance effort and supports sustainable quality at scale.
Why Selenium with Java Training Is Important in Modern DevOps & Software Delivery
Continuous integration and delivery require testing to run automatically with every change. Manual testing cannot meet this speed or consistency. Selenium with Java enables reliable regression testing that executes on each build and deployment. Organizations adopt Selenium because it supports multiple browsers, integrates with DevOps toolchains, and operates across cloud environments. It addresses delayed feedback, inconsistent coverage, and unstable releases. Selenium with Java Training aligns testing with Agile sprints, CI/CD pipelines, and cloud-native delivery. It embeds quality into the delivery process instead of treating it as a final checkpoint.
Why this matters: Automated testing enables rapid, reliable releases without increasing production risk.
Core Concepts & Key Components
Selenium WebDriver
Purpose: Automate browser interactions end to end.
How it works: WebDriver communicates directly with browser drivers.
Where it is used: Functional and regression testing.
Java Programming Foundations
Purpose: Build structured and reusable automation logic.
How it works: Java applies object-oriented design principles.
Where it is used: Framework utilities and test logic.
Locators and Web Elements
Purpose: Identify UI components precisely.
How it works: Locators use ID, name, XPath, or CSS selectors.
Where it is used: Page interaction layers.
Automation Test Frameworks
Purpose: Organize, execute, and manage tests.
How it works: Frameworks like TestNG control execution flow and grouping.
Where it is used: Enterprise automation suites.
Page Object Model (POM)
Purpose: Improve test readability and maintenance.
How it works: Page classes encapsulate locators and actions.
Where it is used: Large-scale automation projects.
Synchronization and Wait Strategies
Purpose: Handle dynamic content and timing issues.
How it works: Explicit waits synchronize actions with UI state.
Where it is used: JavaScript-heavy applications.
Cross-Browser Testing
Purpose: Ensure consistent behavior across browsers.
How it works: Tests execute on multiple browser engines.
Where it is used: Customer-facing applications.
Test Data Management
Purpose: Support varied input scenarios.
How it works: External data sources drive test execution.
Where it is used: Regression and data-driven tests.
Reporting and Logging
Purpose: Provide execution visibility and diagnostics.
How it works: Reports summarize results and failures.
Where it is used: QA, DevOps, and stakeholder feedback.
CI/CD Integration
Purpose: Automate test execution within pipelines.
How it works: Builds trigger test runs automatically.
Where it is used: Continuous delivery workflows.
Why this matters: Mastery of these components enables scalable, reliable test automation.
How Selenium with Java Training Works (Step-by-Step Workflow)
Training starts by establishing Selenium and Java fundamentals. Learners automate basic browser actions and validations. Next, they design structured frameworks using Page Object Model patterns. Automation expands to manage synchronization, dynamic elements, and cross-browser execution. Teams integrate tests into CI/CD pipelines to ensure continuous validation. Reporting and logs deliver rapid feedback to developers and QA teams. Real DevOps lifecycle scenarios demonstrate how automation supports frequent releases without slowing delivery.
Why this matters: A clear workflow ensures automation evolves in a controlled, maintainable way.
Real-World Use Cases & Scenarios
E-commerce teams automate product search, cart, and checkout flows. Financial services validate authentication and transaction journeys. SaaS companies execute regression suites on every deployment. Developers use automation to catch UI issues early. QA teams maintain coverage across browsers and environments. DevOps engineers embed tests into pipelines. SRE teams monitor UI reliability after releases. Organizations reduce defects and deliver consistent experiences to users at scale.
Why this matters: Practical use cases show automation directly improves business outcomes.
Benefits of Using Selenium with Java Training
Productivity: Faster execution and reduced manual effort Reliability: Consistent results across environments Scalability: Automation grows with application complexity Collaboration: Shared ownership across Dev, QA, and DevOps Why this matters: Skilled teams maintain quality while accelerating delivery.
Challenges, Risks & Common Mistakes
Teams often create brittle tests that break after UI changes. Weak locator strategies increase maintenance cost. Poor synchronization leads to flaky runs. Some teams start automation too late in the lifecycle. Selenium with Java Training addresses these risks by teaching framework design, best practices, and DevOps-aligned testing strategies. Learners understand what to automate, when to automate, and how to keep tests stable.
Why this matters: Avoiding common pitfalls preserves automation value over time.
Comparison Table
AspectManual TestingSelenium with JavaExecution SpeedSlowFastConsistencyLowHighScalabilityLimitedStrongCI/CD SupportWeakNativeAccuracyVariableStableCoveragePartialExtensiveCost Over TimeHighLowerReportingManualAutomatedTeam CollaborationSiloedIntegratedEnterprise ReadinessLowHigh Why this matters: The comparison explains why teams adopt automation for modern delivery.
Best Practices & Expert Recommendations
Teams should structure automation using Page Object Model. Engineers should prefer stable locators and manage waits carefully. Tests should run early and often within CI/CD pipelines. Automation code should follow software engineering standards and version control. Regular refactoring keeps suites healthy and reliable.
Why this matters: Best practices ensure long-term stability and scalability.
Who Should Learn or Use Selenium with Java Training?
QA engineers build and maintain automated suites. Developers validate UI behavior early. DevOps engineers integrate tests into delivery pipelines. Cloud and SRE teams rely on automation to detect UI regressions. Beginners gain strong foundations, while experienced professionals enhance enterprise automation skills.
Why this matters: Proper audience alignment delivers immediate, practical value.
FAQs – People Also Ask
What is Selenium with Java Training?
It teaches automated web testing using Selenium and Java.
Why this matters: It defines the learning scope.
Is it suitable for beginners?
Yes, basic programming knowledge is sufficient.
Why this matters: New learners can start confidently.
Is it relevant for DevOps roles?
Yes, it integrates with CI/CD pipelines.
Why this matters: DevOps depends on automation.
Does it support multiple browsers?
Yes, Selenium supports major browsers.
Why this matters: Applications run on diverse platforms.
Is Selenium still widely used?
Yes, many enterprises rely on it.
Why this matters: Skills remain future-proof.
Does it support cloud-based testing?
Yes, with Selenium Grid and cloud services.
Why this matters: Cloud testing continues to grow.
Is Java mandatory?
Java is a preferred enterprise option.
Why this matters: Enterprises value Java stability.
Can developers use Selenium?
Yes, developers automate UI validations.
Why this matters: Shared testing improves quality.
Does automation replace manual testing?
No, both complement each other.
Why this matters: Balanced testing ensures reliability.
Is framework design important?
Yes, it reduces maintenance effort.
Why this matters: Poor design increases long-term cost.
Branding & Authority
DevOpsSchool delivers globally trusted, enterprise-grade training in DevOps, automation, cloud, and quality engineering. The platform emphasizes hands-on labs, real project scenarios, and curricula aligned with industry expectations. DevOpsSchool helps professionals build skills that translate directly into production-ready performance and sustainable career growth.
Why this matters: Trusted training ensures learning leads to real operational capability.
Rajesh Kumar brings over 20 years of hands-on expertise across DevOps & DevSecOps, Site Reliability Engineering (SRE), DataOps, AIOps & MLOps, Kubernetes & Cloud Platforms, and CI/CD & Automation. His mentorship blends technical depth with enterprise execution, enabling learners to build reliable, scalable automation solutions.
Why this matters: Experienced guidance strengthens credibility and learning outcomes.
Call to Action & Contact Information
Explore the complete Selenium with Java Training program and start building CI/CD-ready test automation skills today.
Email: [email protected]
Phone & WhatsApp (India): +91 7004215841
Phone & WhatsApp (USA): +1 (469) 756-6329



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OpenShift Cluster Management: A Comprehensive Guide

Introduction: Problem, Context & Outcome
Organizations increasingly build and run applications on container platforms, yet many engineering teams struggle to operate these platforms reliably at scale. OpenShift clusters involve multiple moving parts such as access control, networking, storage, upgrades, and continuous availability. When teams lack strong platform administration skills, even small configuration errors can cause outages, slow releases, or security issues. Enterprises adopt OpenShift to bring control, consistency, and security to Kubernetes-based environments across cloud and on-prem infrastructure. The Red Hat Certified Specialist in OpenShift Administration addresses this need by validating real operational skills required to run OpenShift in production. This certification-focused learning helps professionals understand platform responsibilities, operational workflows, and enterprise expectations. Readers gain clarity on how OpenShift administrators support stable DevOps pipelines and business-critical workloads.
Why this matters: Effective OpenShift administration directly influences platform reliability, security, and delivery speed.
What Is Red Hat Certified Specialist in OpenShift Administration?
Red Hat Certified Specialist in OpenShift Administration is a hands-on certification that measures a professional’s ability to manage and maintain OpenShift clusters in real-world environments. It focuses on practical administrative tasks such as managing projects and users, configuring networking and storage, controlling container images, monitoring cluster health, and performing upgrades. DevOps engineers, platform engineers, and SRE teams rely on these capabilities to keep container platforms stable and predictable. The certification builds on Kubernetes fundamentals and extends them with Red Hat’s enterprise features for governance and security. In production environments, OpenShift administrators ensure developers can deploy applications confidently through CI/CD pipelines. This certification demonstrates readiness to manage OpenShift under real operational pressure.
Why this matters: Hands-on validation proves that administrators can manage live clusters, not just understand concepts.
Why Red Hat Certified Specialist in OpenShift Administration Is Important in Modern DevOps & Software Delivery
Enterprises choose OpenShift to standardize container operations and reduce the operational complexity of Kubernetes. While OpenShift simplifies many tasks, successful adoption still depends on skilled administration. DevOps teams rely on stable OpenShift platforms to deliver applications continuously and securely. Weak administration leads to failed deployments, unreliable pipelines, and compliance risks. The Red Hat Certified Specialist in OpenShift Administration ensures professionals understand how OpenShift integrates with CI/CD tools, authentication systems, monitoring solutions, and cloud platforms. Agile and DevOps practices depend on platforms that remain stable even under frequent change. Certified administrators help organizations balance speed, control, and reliability.
Why this matters: Skilled OpenShift administrators enable secure and scalable DevOps delivery.
Core Concepts & Key Components
OpenShift Cluster Architecture
Purpose: Define how control plane and worker nodes operate together.
How it works: OpenShift runs Kubernetes with enterprise enhancements.
Where it is used: Enterprise container platforms.
Projects and Namespaces
Purpose: Separate workloads and teams securely.
How it works: Projects group resources with policies and quotas.
Where it is used: Multi-team clusters.
Role-Based Access Control (RBAC)
Purpose: Regulate user and service permissions.
How it works: Roles and bindings define allowed actions.
Where it is used: Security and governance.
Networking and Routes
Purpose: Expose applications safely to users.
How it works: Routes manage ingress traffic and TLS.
Where it is used: Application access.
Persistent Storage
Purpose: Preserve data beyond pod lifecycles.
How it works: Persistent volumes connect storage backends.
Where it is used: Stateful workloads.
Operators
Purpose: Automate application and platform lifecycle tasks.
How it works: Operators manage deployment and updates.
Where it is used: Platform automation.
Monitoring and Logging
Purpose: Observe performance and health.
How it works: Metrics and logs provide visibility.
Where it is used: Reliability and troubleshooting.
Image Streams
Purpose: Manage container image versions.
How it works: Image streams track and update images.
Where it is used: Secure deployments.
Resource and Scaling Management
Purpose: Control resource usage and growth.
How it works: Requests, limits, and autoscaling manage capacity.
Where it is used: High-traffic applications.
Cluster Updates and Maintenance
Purpose: Keep clusters secure and current.
How it works: Controlled upgrades reduce downtime.
Where it is used: Production environments.
Why this matters: These components define the daily responsibilities of OpenShift administrators.
How Red Hat Certified Specialist in OpenShift Administration Works (Step-by-Step Workflow)
Administrators begin by validating cluster configuration and overall health. They create projects and apply RBAC policies to control access. Teams deploy applications using approved images and templates. Administrators expose services through routes and attach persistent storage when needed. Monitoring and logging tools track performance and identify issues early. CI/CD pipelines deliver application updates continuously while administrators manage scaling and upgrades. This structured workflow mirrors real DevOps lifecycles and supports rapid delivery without compromising stability.
Why this matters: Clear operational workflows reduce misconfiguration and prevent production outages.
Real-World Use Cases & Scenarios
Retail platforms depend on OpenShift administrators to handle traffic spikes during promotions. Financial organizations rely on strict access controls and compliance enforcement. DevOps engineers deploy microservices through automated pipelines. Developers work within isolated namespaces for faster iteration. QA teams validate releases in controlled environments. SRE teams monitor availability and scale clusters during peak demand. Cloud engineers manage OpenShift across hybrid and multi-cloud environments. Businesses achieve faster releases with lower operational risk.
Why this matters: Real-world scenarios show how OpenShift administration impacts business performance.
Benefits of Using Red Hat Certified Specialist in OpenShift Administration
Productivity: Faster issue resolution and platform management Reliability: Stable clusters with reduced downtime Scalability: Predictable growth of applications and infrastructure Collaboration: Clear separation of platform and application responsibilities Why this matters: Certified administrators provide dependable platforms that teams trust.
Challenges, Risks & Common Mistakes
Teams often misconfigure RBAC and expose sensitive resources. Poor resource limits create instability under load. Inadequate monitoring delays incident detection. Unplanned upgrades introduce outages. Certification-aligned training addresses these risks through hands-on scenarios and operational best practices. Administrators learn to identify issues early and maintain platform stability.
Why this matters: Avoiding common mistakes protects uptime and business continuity.
Comparison Table
AspectInformal OpenShift ManagementCertified OpenShift AdministrationPlatform KnowledgeInconsistentValidatedSecurity ControlsWeakStrongCI/CD StabilityUnpredictableReliableTroubleshootingReactiveProactiveScaling StrategyManualStructuredCompliance ReadinessLimitedEnterprise-readyDowntime RiskHighReducedAutomation UsagePartialMatureUpgrade PlanningRiskyControlledEnterprise ConfidenceLowHigh Why this matters: The comparison highlights the business value of certified expertise.
Best Practices & Expert Recommendations
Administrators should apply RBAC strictly and monitor clusters continuously. Teams should automate backups and upgrades. Engineers should define resource quotas and document platform standards clearly. CI/CD integration should follow OpenShift best practices. Continuous learning keeps administrators aligned with platform evolution.
Why this matters: Best practices sustain long-term platform stability and security.
Who Should Learn or Use Red Hat Certified Specialist in OpenShift Administration?
DevOps engineers operate delivery pipelines on OpenShift. Platform engineers manage Kubernetes-based systems. Cloud engineers oversee hybrid deployments. SRE teams focus on reliability and scaling. Developers benefit from understanding platform constraints. Beginners build solid foundations, while experienced professionals validate enterprise-level expertise.
Why this matters: Role-aligned learning delivers measurable career and organizational value.
FAQs – People Also Ask
What is Red Hat Certified Specialist in OpenShift Administration?
It validates hands-on OpenShift operational skills.
Why this matters: It proves real production readiness.
Is this certification suitable for beginners?
It suits learners with basic Kubernetes knowledge.
Why this matters: Proper preparation improves success.
Is it relevant for DevOps roles?
Yes, DevOps teams rely on OpenShift platforms.
Why this matters: Skills align with industry demand.
Does it include CI/CD workflows?
Yes, OpenShift supports pipeline-based deployments.
Why this matters: CI/CD depends on stable platforms.
Do enterprises widely use OpenShift?
Yes, across regulated and large-scale environments.
Why this matters: Enterprise adoption ensures relevance.
How does it differ from Kubernetes admin certifications?
It focuses on Red Hat enterprise tooling.
Why this matters: Tool-specific expertise matters in jobs.
Does it cover security topics?
Yes, RBAC and policy management are core.
Why this matters: Security remains critical.
Does the exam test practical skills?
Yes, it emphasizes real operational tasks.
Why this matters: Hands-on ability drives success.
Can it support hybrid cloud environments?
Yes, OpenShift runs across clouds.
Why this matters: Hybrid adoption continues to grow.
Does certification support career growth?
Yes, employers value certified administrators.
Why this matters: Certification strengthens professional credibility.
Branding & Authority
DevOpsSchool delivers globally trusted, enterprise-grade training across DevOps, cloud computing, Kubernetes, OpenShift, and automation. The platform emphasizes hands-on labs, real production scenarios, and skills aligned with enterprise expectations. DevOpsSchool helps professionals build platform expertise that organizations rely on for mission-critical systems.
Why this matters: Trusted training ensures learning translates into real operational capability.
Rajesh Kumar brings more than 20 years of hands-on expertise across DevOps & DevSecOps, Site Reliability Engineering (SRE), DataOps, AIOps & MLOps, Kubernetes & Cloud Platforms, and CI/CD & Automation. His mentorship connects deep technical knowledge with enterprise execution, enabling learners to manage OpenShift platforms confidently at scale.
Why this matters: Proven leadership enhances credibility and learning effectiveness.
Call to Action & Contact Information
Explore official training aligned with this certification here:
Red Hat Certified Specialist in OpenShift Administration training
Email: [email protected]
Phone & WhatsApp (India): +91 7004215841
Phone & WhatsApp (USA): +1 (469) 756-6329




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Ansible Automation Skills: A Comprehensive Guide

Introduction: Problem, Context & Outcome
Engineering teams manage increasingly complex infrastructure across cloud platforms, data centers, and hybrid environments. Manual configuration, shell scripts, and environment-specific fixes create inconsistency, slow delivery, and operational risk. As organizations scale applications and shorten release cycles, teams struggle with configuration drift, deployment failures, and unreliable environments. DevOps practices demand automation that works predictably across systems without adding overhead or complexity. Ansible Certification Training addresses these challenges by teaching professionals how to automate infrastructure and operations using a simple, agentless automation model. This training helps engineers replace manual effort with structured automation that supports reliable, scalable software delivery in real enterprise environments.
Why this matters: Automation directly reduces failures, improves delivery speed, and stabilizes growing infrastructure.
What Is Ansible Certification Training?
Ansible Certification Training is a structured learning program that teaches automation using Ansible while preparing learners for industry-recognized certification exams. The training focuses on configuration management, application deployment, orchestration, and operational automation using human-readable YAML playbooks. Ansible’s agentless design allows teams to adopt automation quickly without installing software on managed systems. Developers and DevOps engineers use this training to automate cloud resources, servers, and services consistently. The curriculum connects Ansible concepts with real production scenarios such as patching, system hardening, environment provisioning, and CI/CD integration. By completing the training, learners gain practical automation skills along with certification readiness that aligns with enterprise DevOps expectations.
Why this matters: Structured learning prevents fragile automation and supports long-term maintainability.
Why Ansible Certification Training Is Important in Modern DevOps & Software Delivery
Modern DevOps workflows depend on automation to achieve continuous integration, continuous delivery, and operational reliability. Ansible plays a central role because it enables infrastructure as code without requiring agents or complex tooling. Organizations across industries rely on Ansible to manage operating systems, cloud infrastructure, network devices, and container platforms. Automation eliminates configuration drift, reduces manual errors, and improves deployment consistency. Ansible integrates easily with CI/CD pipelines and fits Agile and cloud-native delivery models. Ansible Certification Training equips professionals with validated skills that help organizations standardize automation while meeting security and compliance requirements.
Why this matters: Certified automation skills strengthen delivery pipelines and reduce operational risk.
Core Concepts & Key Components
Inventory Management
Purpose: Define systems under automation control.
How it works: Hosts and groups are defined statically or dynamically.
Where it is used: Servers, cloud instances, and network devices.
Playbooks
Purpose: Describe automation workflows.
How it works: YAML files define ordered tasks.
Where it is used: Configuration management and deployments.
Modules
Purpose: Perform specific automation actions.
How it works: Built-in modules execute system operations.
Where it is used: Packages, users, files, and services.
Roles
Purpose: Organize automation logically.
How it works: Standard directory structures group tasks and variables.
Where it is used: Enterprise automation projects.
Variables
Purpose: Customize automation behavior.
How it works: Values modify execution dynamically.
Where it is used: Environment-specific automation.
Facts
Purpose: Collect system information.
How it works: Ansible gathers host metadata automatically.
Where it is used: Conditional execution.
Handlers
Purpose: Execute tasks when changes occur.
How it works: Tasks notify handlers.
Where it is used: Restarting or reloading services.
Templates
Purpose: Generate dynamic configuration files.
How it works: Jinja2 templates insert variables.
Where it is used: Application and system configuration.
Ansible Vault
Purpose: Protect sensitive data.
How it works: Vault encrypts secrets and credentials.
Where it is used: Passwords, API keys, tokens.
Automation Controller
Purpose: Centralize automation operations.
How it works: Provides scheduling, RBAC, and auditing.
Where it is used: Large-scale enterprise environments.
Why this matters: Mastering these components enables secure, scalable, and reusable automation.
How Ansible Certification Training Works (Step-by-Step Workflow)
The training starts with Ansible fundamentals and explains agentless automation clearly. Learners configure inventories and build simple playbooks to automate common administrative tasks. The course introduces roles and variables to structure automation for reuse. Learners then integrate Ansible into CI/CD pipelines to support automated deployments. Security practices cover secret management using Ansible Vault. Advanced topics include orchestration, error handling, and scaling automation through controllers. Real DevOps lifecycle examples show how teams apply Ansible in production environments.
Why this matters: A structured workflow guides learners from basics to enterprise-grade automation.
Real-World Use Cases & Scenarios
Organizations use Ansible to provision infrastructure across AWS, Azure, and on-premise systems. DevOps teams automate application deployments, operating system patching, and configuration updates. Developers maintain consistent development and staging environments with Ansible. QA teams create repeatable test environments quickly. SRE teams rely on automation for operational consistency and incident response. Cloud teams manage hybrid and multi-cloud infrastructure using a unified automation framework.
Why this matters: Real-world adoption proves automation improves delivery speed and reliability.
Benefits of Using Ansible Certification Training
Productivity: Faster automation with reduced manual effort Reliability: Consistent configurations across environments Scalability: Easy management of infrastructure growth Collaboration: Shared automation standards across teams Why this matters: Trained teams deliver stable automation that supports business growth.
Challenges, Risks & Common Mistakes
Teams often create unstructured playbooks that become difficult to maintain. Ignoring idempotency leads to repeated failures. Poor secret management introduces security risks. Some teams misuse Ansible for workflows better handled by other tools. Ansible Certification Training addresses these risks by teaching design principles, best practices, and correct tool usage aligned with enterprise environments.
Why this matters: Awareness of risks protects infrastructure and automation investments.
Comparison Table
AspectManual OperationsAnsible AutomationConfigurationManual stepsAutomated playbooksError RateHighLowConsistencyPoorStrongScalabilityLimitedHighSecurityRisk-proneControlledCI/CD IntegrationWeakNativeMaintenanceDifficultSimpleAuditabilityLowHighCollaborationLimitedStrongEnterprise ReadinessLowHigh Why this matters: Clear comparison shows why teams replace manual operations with automation.
Best Practices & Expert Recommendations
Teams should structure automation with roles and keep playbooks readable. Engineers should enforce idempotency and store secrets securely using Ansible Vault. Teams should test automation in staging environments before production deployment. Version control and documentation should accompany all automation code. Integration with CI/CD pipelines ensures consistent delivery.
Why this matters: Best practices keep automation reliable, secure, and scalable.
Who Should Learn or Use Ansible Certification Training?
Developers benefit from understanding deployment automation. DevOps engineers use Ansible for CI/CD and infrastructure automation. Cloud engineers manage hybrid environments efficiently. SRE teams improve system reliability through consistent configuration. QA teams automate environment provisioning. Beginners and experienced professionals both gain practical, enterprise-ready skills.
Why this matters: Clear role alignment ensures meaningful learning outcomes.
FAQs – People Also Ask
What is Ansible Certification Training?
It teaches Ansible automation and certification skills.
Why this matters: It clarifies learning objectives.
Is Ansible beginner-friendly?
Yes, YAML syntax keeps it simple.
Why this matters: Beginners learn faster.
Is Ansible relevant for DevOps roles?
Yes, teams use it widely in CI/CD pipelines.
Why this matters: Skills align with industry demand.
Does Ansible work with cloud platforms?
Yes, it supports major cloud providers.
Why this matters: Hybrid automation becomes easier.
Do learners need programming skills?
No advanced programming skills are required.
Why this matters: More professionals can adopt automation.
Which certification does this training support?
It supports Red Hat Ansible automation certifications.
Why this matters: Certifications support career growth.
How does Ansible compare with Chef?
Ansible uses agentless automation and simpler setup.
Why this matters: Easier adoption reduces friction.
Can Ansible manage containers?
Yes, it automates container-related tasks.
Why this matters: Modern workloads need automation.
Does Ansible secure sensitive data?
Yes, Vault encrypts secrets.
Why this matters: Security remains critical.
Do enterprises use Ansible?
Yes, organizations use it widely.
Why this matters: Long-term relevance stays strong.
Branding & Authority
DevOpsSchool is a globally trusted platform that delivers enterprise-grade training in DevOps, cloud computing, automation, and emerging technologies. The platform emphasizes real-world execution, operational maturity, and long-term skill relevance. DevOpsSchool programs help professionals and enterprises build automation capabilities that match production environments and industry standards.
Why this matters: Trusted training ensures skills transfer directly to real projects.
Rajesh Kumar brings over 20 years of hands-on experience across DevOps, DevSecOps, Site Reliability Engineering (SRE), DataOps, AIOps, MLOps, Kubernetes, cloud platforms, and CI/CD automation. His mentorship connects theory with enterprise execution and helps learners apply automation confidently at scale.
Why this matters: Experienced guidance increases credibility and learning effectiveness.
Call to Action & Contact Information
Explore the Ansible Certification Training and start automating infrastructure with confidence today.
Email: [email protected]
Phone & WhatsApp (India): +91 7004215841
Phone & WhatsApp (USA): +1 (469) 756-6329




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Quantum Computing Use Cases: A Comprehensive Guide

Introduction: Problem, Context & Outcome
Engineering teams increasingly run into computational limits that traditional systems cannot efficiently overcome. Use cases such as large-scale optimization, encryption resilience, complex simulations, and probabilistic modeling continue to grow as cloud platforms, AI pipelines, and data-driven applications scale. Even the most optimized classical infrastructure struggles with certain categories of exponential problems. Quantum computing introduces a new computational approach that addresses these challenges by leveraging principles of quantum mechanics rather than binary logic alone. Enterprises across industries are now evaluating quantum readiness and long-term skill strategies to stay ahead of innovation curves. The Quantum Computing Training and Certification Course helps professionals understand this shift clearly and practically, without excessive theory. Learners walk away with structured knowledge, enterprise context, and confidence to engage with quantum initiatives responsibly.
Why this matters: Understanding quantum computing early enables teams to influence future architecture decisions instead of reacting after disruption occurs.
What Is Quantum Computing Training and Certification Course?
Quantum Computing Training and Certification Course is a structured learning program that explains how quantum computers operate, how they differ fundamentally from classical machines, and how they fit into real-world enterprise environments. The course covers essential concepts such as qubits, superposition, entanglement, quantum gates, and quantum circuits using clear, engineering-friendly explanations. Rather than focusing on abstract physics, the curriculum emphasizes practical understanding and system-level thinking. Developers and DevOps professionals learn how quantum algorithms solve specific problems differently and where quantum advantage actually applies. The course also introduces hybrid quantum-classical architectures, cloud-based quantum access, and operational considerations relevant to modern software delivery teams.
Why this matters: Practical clarity helps professionals evaluate quantum computing objectively and avoid misunderstanding or unrealistic expectations.
Why Quantum Computing Training and Certification Course Is Important in Modern DevOps & Software Delivery
Modern DevOps practices prioritize automation, reliability, scalability, and continuous delivery. However, some emerging computational problems exceed the capability of classical processing models. Quantum computing provides alternative approaches for advanced optimization, secure cryptography, scientific simulations, and probabilistic modeling. With cloud providers offering managed quantum services, experimentation now happens within real DevOps environments instead of isolated research labs. DevOps teams must understand how quantum workloads differ in execution patterns, testing strategies, cost models, and observability requirements. This course equips professionals with the knowledge needed to integrate quantum exploration safely into CI/CD workflows and cloud-native systems. It also helps organizations distinguish between near-term experimentation and long-term production readiness.
Why this matters: Quantum-aware DevOps teams can shape innovation strategy instead of becoming blockers or late adopters.
Core Concepts & Key Components
Qubits
Purpose: Represent data in quantum systems beyond binary logic.
How it works: Qubits can exist in multiple states at the same time through superposition.
Where it is used: Quantum algorithms and simulations.
Superposition
Purpose: Enable probabilistic parallel computation.
How it works: A qubit holds multiple possible values until measurement.
Where it is used: Search, optimization, and modeling tasks.
Entanglement
Purpose: Create correlated behavior between qubits.
How it works: The state of one qubit instantly affects another.
Where it is used: Secure communication and quantum networking.
Quantum Gates
Purpose: Perform logical operations on qubits.
How it works: Mathematical transformations alter quantum states.
Where it is used: Building quantum circuits.
Quantum Circuits
Purpose: Define the workflow of quantum computation.
How it works: Ordered sequences of quantum gates operate on qubits.
Where it is used: Algorithm execution and experimentation.
Quantum Algorithms
Purpose: Solve specific problems more efficiently than classical methods.
How it works: Algorithms exploit superposition and entanglement.
Where it is used: Cryptography, chemistry, optimization.
Measurement
Purpose: Extract classical results from quantum states.
How it works: Measurement collapses quantum states into definite values.
Where it is used: Result validation.
Quantum Error Correction
Purpose: Reduce instability and noise.
How it works: Logical qubits protect physical qubits through redundancy.
Where it is used: Enterprise and research environments.
Hybrid Quantum-Classical Systems
Purpose: Combine quantum processing with existing systems.
How it works: Classical infrastructure controls and integrates quantum tasks.
Where it is used: Practical enterprise experimentation.
Quantum Cloud Platforms
Purpose: Provide access to quantum hardware without physical ownership.
How it works: Cloud providers expose quantum processors via managed services.
Where it is used: Learning, testing, and early adoption.
Why this matters: Understanding foundational components allows teams to assess real-world feasibility without hype.
How Quantum Computing Training and Certification Course Works (Step-by-Step Workflow)
The course begins by establishing clear conceptual understanding of quantum principles using engineering analogies. Learners then identify which problem types benefit from quantum approaches and which do not. Next, quantum circuits and execution flows are introduced at a high level without heavy mathematics. Practical examples show how quantum workloads integrate with cloud platforms alongside existing DevOps pipelines. Governance, cost control, access management, and security considerations follow to ensure safe experimentation. Certification validates understanding and prepares learners for future-ready roles.
Why this matters: A structured workflow ensures learning progresses from understanding to responsible application.
Real-World Use Cases & Scenarios
Financial organizations explore quantum optimization for portfolio risk analysis. Pharmaceutical companies evaluate molecular simulations to accelerate drug discovery. Logistics providers investigate scheduling and route optimization problems. DevOps engineers manage hybrid pipelines where classical systems preprocess data and quantum systems perform advanced computations. QA teams validate probabilistic results, while SRE teams monitor reliability and cost. Business leaders gain insights that support innovation without disrupting delivery stability.
Why this matters: Real-world scenarios demonstrate tangible business and engineering value.
Benefits of Using Quantum Computing Training and Certification Course
Productivity: Faster comprehension of advanced computing paradigms Reliability: Reduced experimentation risk through informed decisions Scalability: Preparation for next-generation workloads Collaboration: Shared understanding across teams Innovation: Enables future-focused solution design Why this matters: Education maximizes long-term benefits while minimizing operational risk.
Challenges, Risks & Common Mistakes
Common mistakes include assuming quantum advantages apply universally, underestimating hardware instability, or investing too early without governance. Teams sometimes pursue quantum initiatives disconnected from real business problems. This course addresses these risks by emphasizing problem suitability, phased adoption, and hybrid architectures aligned with DevOps practices.
Why this matters: Awareness prevents wasted investment and failed initiatives.
Comparison Table
AspectClassical ComputingQuantum ComputingData UnitBitQubitProcessingDeterministicProbabilisticHardware MaturityMatureEmergingError RatesLowHighUse CasesGeneral-purposeSpecializedDevOps IntegrationNativeHybridCost PredictabilityHighExperimentalSecurity ApproachClassical cryptographyPost-quantum awareScalabilityLinearProblem-dependentAdoption RiskLowMedium to High Why this matters: Side-by-side comparison supports informed architectural and investment decisions.
Best Practices & Expert Recommendations
Start with education before experimentation. Focus on problems suited for quantum advantage rather than novelty. Use cloud-based quantum access to control cost and risk. Integrate quantum tasks alongside existing CI/CD pipelines without disruption. Establish governance, security, and cross-team collaboration early.
Why this matters: Best practices ensure responsible, scalable exploration.
Who Should Learn or Use Quantum Computing Training and Certification Course?
Developers gain insight into advanced computation models. DevOps engineers understand future infrastructure implications. Cloud architects learn hybrid integration strategies. QA and SRE professionals become familiar with validation and reliability challenges. The course suits beginners and experienced professionals alike.
Why this matters: Correct audience alignment ensures meaningful learning outcomes.
FAQs – People Also Ask
What is quantum computing?
A computing approach based on quantum mechanics.
Why this matters: Establishes foundational clarity.
Is quantum computing used today?
Yes, mainly for research and experimentation.
Why this matters: Sets realistic expectations.
Is this course beginner-friendly?
Yes, it starts from fundamentals.
Why this matters: Encourages broader adoption.
Does quantum replace classical computing?
No, it complements classical systems.
Why this matters: Prevents misconceptions.
Is quantum relevant for DevOps roles?
Yes, through hybrid workflows.
Why this matters: Aligns skills with roles.
Do I need physics knowledge?
No, concepts are simplified.
Why this matters: Lowers entry barriers.
Which industries use quantum computing?
Finance, pharmaceuticals, logistics, research.
Why this matters: Shows enterprise relevance.
Is certification valuable?
Yes, it validates future-ready skills.
Why this matters: Supports career progression.
When should companies adopt quantum?
Gradually, starting with education.
Why this matters: Enables safe adoption.
Is cloud access required?
Usually, yes.
Why this matters: Clarifies infrastructure needs.
Branding & Authority
DevOpsSchool is a globally trusted training platform delivering enterprise-grade programs in DevOps, cloud computing, automation, and emerging technologies. The platform focuses on real-world execution, operational maturity, and long-term relevance rather than trend-based theory. Through programs such as the Quantum Computing Training and Certification Course, DevOpsSchool helps professionals and organizations prepare responsibly for next-generation computing challenges while maintaining governance and delivery excellence.
Why this matters: Learning from credible institutions ensures advanced skills translate into real operational capability.
Rajesh Kumar is a seasoned technology mentor with more than 20 years of hands-on experience across DevOps, DevSecOps, Site Reliability Engineering, DataOps, AIOps, MLOps, Kubernetes, cloud platforms, and CI/CD automation. His mentorship blends technical depth with enterprise realism, helping learners approach complex technologies like quantum computing with confidence and clarity.
Why this matters: Proven experience builds trust and ensures future-ready learning outcomes.
Call to Action & Contact Information
Explore the Quantum Computing Training and Certification Course and begin building future-ready computing expertise today.
Email: [email protected]
Phone & WhatsApp (India): +91 7004215841
Phone & WhatsApp (USA): +1 (469) 756-6329
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Europol Arrests 34 Black Axe Members in Spain Over €5.9M Fraud and Organized Crime

Europol on Friday announced the arrest of 34 individuals in Spain who are alleged to be part of an international criminal organization called Black Axe. As part of an operation conducted by the Spanish National Police, in coordination with the Bavarian State Criminal Police Office and Europol, 28 arrests were made in Seville, along with three others in Madrid, two in Málaga, and one in BarcelonaView the full article
Hacker News

Best Cosmetic Hospitals: The One-Stop Platform for Cosmetic Surgery & Medical Tourism Worldwide

Planning cosmetic surgery is a big decision. Patients want safe options, trusted providers, clear information, and the best value—especially when exploring treatment abroad. That’s why Best Cosmetic Hospitals is designed as a one-stop platform for cosmetic surgery and medical tourism, helping people discover world-class care, understand procedures, and make confident choices across global destinations.
Whether you are researching a facelift, rhinoplasty, hair transplant, liposuction, tummy tuck, breast surgery, or non-surgical cosmetic treatments, Best Cosmetic Hospitals brings all key information together—so you can compare options and move forward with clarity.
Why Best Cosmetic Hospitals Is Trusted by Patients
Best Cosmetic Hospitals focuses on what patients need most: reliable cosmetic surgery information, access to leading providers, and medical tourism guidance. Instead of searching across multiple websites and sources, you can explore hospitals, doctors, treatments, procedures, conditions, and destinations from one platform.
Here’s what makes Best Cosmetic Hospitals different:
A patient-first platform built for cosmetic surgery decision-making Coverage of major surgery categories and non-surgical treatments Information to support medical tourism planning and cost comparison Easy access to hospitals and doctors across top destinations Best Cosmetic Hospitals Services: What You Can Explore
The goal of Best Cosmetic Hospitals is to help patients understand cosmetic surgery options and connect them with trusted information and providers worldwide. The platform supports the full cosmetic surgery journey, including:
Understanding treatment types and who they are best suited for Learning about recovery timelines and expected outcomes Comparing cosmetic surgery destinations for affordability and care quality Finding hospitals, doctors, and procedure information in one place To explore global provider options, visit Best Cosmetic Hospitals Hospitals and browse hospitals by destination and specialty.
Cosmetic Surgeries Covered by Best Cosmetic Hospitals
One of the biggest strengths of Best Cosmetic Hospitals is its wide coverage of cosmetic surgeries and aesthetic procedures. Below are the most searched categories patients explore worldwide.
1) Cosmetic Facial Surgery
Facial surgery focuses on enhancing facial balance and reducing visible signs of aging. Common cosmetic facial procedures include:
Rhinoplasty (nose job) Facelift Eyelid surgery (blepharoplasty) Chin and cheek enhancement Facial contouring and wrinkle correction You can explore more options in Best Cosmetic Hospitals Procedures.
2) Cosmetic Breast Surgery
Breast procedures are among the most requested cosmetic surgeries globally. These commonly include:
Breast augmentation Breast lift Breast reduction Corrective and reconstructive procedures (depending on patient needs) 3) Cosmetic Body Reshaping & Contouring
Body contouring is designed to shape body proportions and address stubborn fat or excess skin. Popular options include:
Liposuction Tummy tuck (abdominoplasty) Arm lift Thigh lift Body contouring combinations For a complete list, see Best Cosmetic Hospitals Procedures.
4) Men’s Cosmetic Procedures
Cosmetic surgery for men continues to grow worldwide. Common men’s procedures include:
Male chest reduction Liposuction Tummy tuck Hair restoration procedures 5) Hair Transplantation
Hair transplantation is one of the most popular cosmetic procedures across many medical tourism destinations due to affordability and expertise.
6) Cosmetic Dentistry
Cosmetic dentistry focuses on improving smile appearance, often including whitening, restoration options, and cosmetic enhancements—commonly combined with medical tourism trips.
Best Cosmetic Hospitals Treatments: Non-Surgical Aesthetic Options
Not everyone wants surgery. Many people choose non-surgical options to improve skin quality, reduce wrinkles, or refresh appearance with minimal downtime.
Explore non-surgical options in Best Cosmetic Hospitals Treatments, including popular categories such as:
Laser-based treatments Skin rejuvenation approaches Non-surgical cosmetic procedures and aesthetic therapies Meet Best Cosmetic Doctors
Choosing the right specialist is just as important as choosing the right procedure. If you are comparing surgeons and specialists by experience, location, and area of expertise, the Best Cosmetic Doctors section helps you explore doctors across cosmetic surgery and aesthetic care fields.
For many patients, starting with Best Cosmetic Doctors makes it easier to shortlist specialists before selecting a hospital or destination.
Best Cosmetic Hospitals Diseases: Understanding Conditions That Impact Treatment
Some patients explore cosmetic procedures alongside skin concerns or conditions that may affect treatment decisions (for example, scarring, pigmentation issues, or other cosmetic-related concerns). The Best Cosmetic Hospitals Diseases section helps patients learn about conditions and how they relate to cosmetic treatments and procedures.
Best Platform for Medical Tourism
Medical tourism is about finding safe, reliable care in global destinations—often with the benefit of cost savings. Best Cosmetic Hospitals is widely used as a best platform for medical tourism because it combines:
Procedure research and treatment education Destination comparison for cosmetic surgery travel Access to hospitals and doctors worldwide A structured way to explore options and plan next steps To explore where patients travel for cosmetic surgery, visit Best Cosmetic Hospitals Destinations.
Quick Links: Explore Best Cosmetic Hospitals by Category
Best Cosmetic Hospitals (Main Platform) Best Cosmetic Hospitals Hospitals Best Cosmetic Doctors Best Cosmetic Hospitals Treatments Best Cosmetic Hospitals Procedures Best Cosmetic Hospitals Diseases Best Cosmetic Hospitals Destinations Final Thoughts
If you want a single, reliable source to explore cosmetic surgery worldwide, compare treatments, understand procedures, and plan a medical tourism journey, Best Cosmetic Hospitals is built for exactly that purpose. From trusted hospitals and Best Cosmetic Doctors to non-surgical treatments, procedures, and destinations, Best Cosmetic Hospitals helps patients take the next step with clarity and confidence.

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Trend Micro patches critical flaws in its Apex Central software

Security company Trend Micro has been compelled to issue a patch for its own Apex Central software management tool after vulnerability management platform Tenable identified several security flaws.
The bugs affect all versions of Apex Central (on-premises) earlier than build 7190.
In a security bulletin, Trend Micro said of the most severe flaw, rated 9.8, “A LoadLibraryEX vulnerability in Trend Micro Apex Central could allow an unauthenticated remote attacker to load an attacker-controlled DLL into a key executable, leading to execution of attacker-supplied code under the context of SYSTEM on affected installations.”
Erik Avakian, technical counselor at Info-Tech Research Group, explained why this is an issue. “There’s a critical flaw in the management server in how one of its background services handles certain types of network messages that allows an attacker on the network to run their own code without logging in. That service will accept a message from anyone on the network and then can blindly load a Windows DLL using a standard Windows function. The problem is that the software doesn’t properly validate where that DLL is coming from.”
When this happens, he said, the affected software will run the attacker’s code, probably at the highest level of privilege. So, in these circumstances, the attacker can point Apex Central to a DLL that they control, for example, on a remote network. That could then move deeper into the corporate software environment. “In short, if this server is exposed and unpatched, it can be taken over remotely,” said Avakian.
What makes the attack particularly insidious, he said, is that attackers don’t need to log into the server or copy files onto it. “They simply can host a malicious DLL somewhere they control and instruct Apex Central to load it. Because of the flaw, Apex Central reaches out and loads the DLL itself, effectively pulling in and executing the attacker’s code without checking who asked.”
He added that the SYSTEM context was important because that means that the vulnerable service is running with maximum privileges. Thus, it would enable the attacker to carry out a wide range of activities, including modifying files, installing or disabling software, creating user accounts, or using the server as a launch point to attack other systems.
The vulnerability does not seem to be the result of recent modifications to the software. Avakian said. “Everything in the published materials indicates this flaw may have been present for some time. The advisory affects all builds below the fixed version, and there’s no indication that it was introduced recently. On the surface, this appears to be a long-standing issue that was only recently discovered and addressed.”
Neither Trend Micro nor Tenable responded to requests for comment by publication time.
In addition to this critical vulnerability, Trend Micro’s bulletin also highlighted two other high severity issues, neither of which requires authentication to be exploited. The first is a message unchecked NULL return value vulnerability in Trend Micro Apex Central that could allow a remote attacker to create a denial-of-service condition on affected installations. The second is a message out-of-bounds read vulnerability in Trend Micro Apex Central that could also allow a remote attacker to create a denial-of-service condition. All three flaws are patched in build 7190.
Trend Micro’s advisory did point out that to exploit vulnerabilities like these, the attacker would generally need access to a vulnerable machine.
However, the company advised customers to review remote access to critical systems to ensure policies and perimeter security are up-to-date. It also warned them to update to the latest builds as soon as possible.
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CSOonline

Identity & Beyond: 2026 Incident Response Predictions

In 2026, incident response (IR) will continue its shift away from traditional malware-centric investigations toward identity-driven intrusions, abuse of trusted cloud services, and low-signal, high-impact activity that blends seamlessly into normal business operations. Rather than relying on technical exploits, threat actors are prioritizing legitimate access, persistence, and operational efficiency, enabling them to evade users, security controls, and automated detection.
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cybereason

ZombieAgent ChatGPT attack shows persistent data leak risks of AI agents

Researchers have found new ways to turn ChatGPT into a data exfiltration tool and even use it as a persistent backdoor. The new ZombieAgent techniques, which have been patched by OpenAI, fed hidden prompts through connected applications such as email and cloud storage to send data back to attackers in ways invisible to users.
Giving AI chatbots access to tools and external data sources to turn them into autonomous agents is among the biggest trends in AI right now. But security experts have repeatedly warned that this connectivity comes at a risk, especially because AI models cannot natively distinguish between passive data and instructions.
This shortcoming makes models susceptible to indirect prompt injection attacks, in which attackers override the user’s or system’s instructions with malicious prompts hidden in external data parsed by AI. This is a common security issue, and the attack surface is huge: documents, emails, web pages — anything the user might feed to the AI model.
The ZombieAgent attack devised by researchers from security firm Radware is no different. It takes advantage of the Connectors feature of ChatGPT, which allows users to link the chatbot to external apps such as email services; cloud storage drives like Google Drive or OneDrive; enterprise chat clients like Teams and Slack; support ticketing systems like Jira; code hosting services like GitHub; and more.
What these services have in common is that attackers can easily get malicious content into them to be parsed by ChatGPT, sometimes in stealthy ways. For example, in HTML emails or documents attackers can hide malicious prompts with white text on a white background, or use very small font size, or include them in disclaimers and page footers that usually get skimmed over by users.
“This combination of broad connector access and invisible or near-invisible prompt injection significantly amplifies the real-world impact and practicality of the attacks we describe,” the Radware researchers said in their report.
Zero-click attacks
In one demonstration, attackers sent an email with hidden prompts to a Gmail account that was linked to ChatGPT via Connectors. Once the user asks ChatGPT to summarize their email inbox, the chatbot opened the inbox, read the malicious email, and followed the instructions inside, which were to exfiltrate the summary to an attacker server.
 OpenAI includes a protection mechanism to block attaching parameters to an URL, but to bypass it, the researchers simply built a dictionary system where every letter had a corresponding URL on their server, then asked ChatGPT to convert the text to a series of URLs and access them. In this way, the researchers could look at their server’s access logs, see the requests and reconstruct the leaked message.
The same URL-based dictionary approach was used by researchers from security firm Tenable in another series of attack demonstrations against ChatGPT in November. Another method of leaking data is to load images with URLs pointing at attackers’ server using Markdown formatting in the ChatGPT interface.
Worm-like propagation
The email attack even has worming capabilities, as the malicious prompts could instruct ChatGPT to scan the inbox, extract addresses from other email messages, exfiltrate those addresses to the attackers using the URL trick, and send similar poisoned messages to those addresses as well.
If the victim is the employee of an organization that uses ChatGPT, the chances are high that they have emails from other colleagues in their inbox and those colleagues could have ChatGPT connected to their email accounts as well. It’s worth noting that Gmail is just an example in this case and the attack would work with any email service that ChatGPT has a connector for, including Microsoft Outlook.
The researchers also showed that the attack works with prompts embedded in documents as well, either files that the victim manually uploads to ChatGPT for analysis or documents shared with them through their cloud storage service.
Enabling a persistent backdoor
ChatGPT uses a Memory feature to remember important information about the user and their past conversations. This can be triggered by the user when the chatbot is asked to remember something, or automatically when ChatGPT determines that certain information is important enough to save for later.
To limit potential abuse, and malicious instructions being saved in memory, the feature is disabled for chats where Connectors are in use. However, the researchers found that ChatGPT can read, create, modify, and delete memories based on instructions inside a file.
This can be used to combine the two attack techniques into a persistent data-leaking backdoor. First, the attacker sends a file to the victim with hidden prompts that modify ChatGPT’s memory to add two instructions: 1) Save to memory all sensitive information shared by the user in chats, and 2) Every time the user sends a message, open their inbox, read the attacker’s email with subject X and execute the prompts inside, which will result in the sensitive information being leaked.
The ability to modify ChatGPT’s memory is also dangerous because it could include important information about the user, such as medical conditions and treatments.
“We also demonstrated non-exfiltration damage, such as manipulating stored medical history and causing harmful, misleading medical advice,” the researchers wrote.
These attack techniques were reported to OpenAI in September and were fixed on Dec. 16, but are unlikely to be the last attacks demonstrated against ChatGPT. Similar vulnerabilities were discovered in other AI chatbots and LLM-powered tools in the past, and because prompt injections don’t have a complete fix, there will always be bypasses to the guardrails put in place to prevent them.
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CSOonline

Apple Reminding Users of Pending Home App Upgrade Requirement

Back in late 2022 and early 2023, Apple rolled out a new architecture for its Apple Home platform to deliver improved performance and compatibility, although the rollout came with some hiccups that forced Apple to pull and later re-release the upgrade.


Three years later, Apple is now on the verge of ending support for the old version of the Home architecture, which may result in access to the entire Home platform being blocked for some users if they do not or cannot update. The deadline for updating was originally announced as fall 2025, but in early November, Apple announced that it was pushing back the deadline to February 10, 2026.

It appears Apple will be sticking with that deadline, as the company is sending out fresh reminder emails today to users who have yet to upgrade to the new version of Apple Home.Users can update to the new version of Apple Home within the Software Update section of Home Settings in the Home app. If you have already completed these steps, or "This home and all accessories are up to date" is shown in Software Update, then you are already on the current version and there is nothing more you need to do.

Notably, the new version of Apple Home requires a minimum of iOS 16.2, iPadOS 16.2, macOS 13.1, tvOS 16.2, and watchOS 9.2, and older devices that have not been or cannot be updated will lose access to the Apple Home after updating. This requirement has not sat well with some users who may use older devices as dedicated Home control devices, so many of these users have put off upgrading their Home architecture for as long as possible, but it now appears the reprieve is coming to an end.Tags: Home, HomeKit
This article, "Apple Reminding Users of Pending Home App Upgrade Requirement" first appeared on MacRumors.com

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U.S. Senators Ask Apple and Google to Remove X and Grok Apps Over Sexualized Image Generation

In a letter to Apple CEO Tim Cook and Google CEO Sundar Pichai, U.S. Senators Ron Wyden, Ben Ray Lujan, and Edward Markey have requested that Apple and Google remove X Corp's X and Grok apps from their app stores over recent incidents of "mass generation of nonconsensual sexualized images of women and children."


X has come under fire over the past week amid reports of Grok's AI image generation capabilities being used to create images depicting women and children in bikinis or underwear. In response, X appears to have scaled back the ability for Grok to generate images in response to X posts by non-paying users, but The Verge notes that the tools remain available to paying subscribers and through the dedicated Grok tab in the X and in the standalone Grok app.

The senators argue that the "harmful and likely illegal depictions" are in violation of Apple's and Google's app store terms and that the two companies must remove the apps until the policy violations are addressed.The senators request a written response to their letter by January 23.Tag: Grok
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China-Linked Hackers Exploit VMware ESXi Zero-Days to Escape Virtual Machines

Chinese-speaking threat actors are suspected to have leveraged a compromised SonicWall VPN appliance as an initial access vector to deploy a VMware ESXi exploit that may have been developed as far back as February 2024. Cybersecurity firm Huntress, which observed the activity in December 2025 and stopped it before it could progress to the final stage, said it may have resulted in a ransomwareView the full article
Hacker News

The First Week Check: What IT Managers Should Validate When Using AI in the SOC

As AI becomes embedded in security operations, many IT and security managers are starting the year with AI already active in their SOC workflows. That’s a positive step — but it also changes what “operational hygiene” looks like.
 
AI doesn’t fail loudly when something is wrong. It fails quietly. That’s why the first week of the year is an ideal time to validate how AI is actually behaving inside the SOC — not in theory, but in daily operations.
 
This isn’t about tuning models or adding new capabilities. It’s about confirming that AI is operating within expected boundaries, under human oversight, and delivering the outcomes it was introduced to achieve.
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compuquip

Apple Wins Another Round in AliveCor Legal Battle Over Heart Rate Tech

Apple this week secured another victory in its ongoing legal dispute with heart monitoring company AliveCor, after a federal appeals court upheld a 2024 ruling that found Apple's changes to the Apple Watch were lawful product improvements rather than anticompetitive behavior.


The Ninth Circuit Court of Appeals affirmed a lower court decision that rejected AliveCor's antitrust claims. AliveCor had argued that Apple illegally monopolized the market for heart rate analysis apps on watchOS when it replaced its Heart Rate during Physical Observation (HRPO) algorithm with its heart rate neural network (HRNN) algorithm in watchOS 5.

AliveCor claimed that Apple changed the algorithm so that its ECG KardiaBand could no longer identify irregular heart rhythms – as part of an alleged effort to "eliminate opposition" in the heart rate analysis space – and requested that it reinstate the old algorithm.

Apple argued that AliveCor did not have the right to dictate Apple's design decisions, and that the request to support the older heart rate technology would require the court to be a day-to-day enforcer of how Apple engineers its products. The court ultimately agreed with Apple.

The Ninth Circuit has now affirmed Apple's victory. "The undisputed evidence shows as a matter of law that Apple's refusal to share HRPO data was not anticompetitive," the court wrote. It added that even if some form of heart rate data access were essential for competing in the market, AliveCor's claim would still fail because Apple provides app developers with access to the same Tachogram API data that Apple's Irregular Rhythm Notification feature uses.

The appeals court also rejected AliveCor's argument that Apple had a duty to share its proprietary data with competitors. The ruling said that antitrust laws generally impose no obligation for companies to deal with their rivals. It also noted that such a requirement "would implicate the same concerns regarding incentives to innovate and judicial competency that the Supreme Court has articulated."

The decision is Apple's second major win against AliveCor within the last year. In March, the Federal Circuit confirmed the invalidation of three AliveCor patents related to heart rate monitoring, vacating an International Trade Commission ruling that could have led to an Apple Watch import ban.

AliveCor said at the time of the court's original ruling that it was "deeply disappointed" by the decision and would continue to explore all available legal options, including potential appeals.Tags: AliveCor, Apple Antitrust, Apple Lawsuits
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Apple Is Expected to Launch These Four MacBooks in 2026

2026 could be a bumper year for Apple's Mac lineup, with the company expected to announce as many as four separate MacBook launches. Rumors suggest Apple will court both ends of the consumer spectrum, with more affordable options for students and feature-rich premium lines for users that seek the highest specifications from a laptop.


Below is a breakdown of what we're expecting over the next 12 months from Apple's multi-pronged MacBook offering. Got your eye on a particular model? Let us know in the comments what you're looking forward to most.

Low-Cost MacBook


Apple is preparing to enter the low-cost laptop market for the first time by developing a budget MacBook aimed at luring away customers from Chromebooks and entry-level Windows PCs, according to Bloomberg's Mark Gurman. The new device is said to be designed for students, businesses, and casual users, and will target people who mainly browse the web, work on documents, or dabble in light media editing.

The new MacBook is said to have a 13-inch display, similar to but slightly smaller than the MacBook Air, and will feature an ultra-thin, lightweight design with a lower-end LCD display. According to reputable industry analyst Ming-Chi Kuo, Apple is said to be using its A18 Pro chip to power the machine. The A18 Pro chip debuted in the iPhone 16 Pro and is around 40% slower than Apple's latest M4 chip, but its multi-core CPU performance is virtually identical to the M1 chip in the 2020 MacBook Air, and it even outperforms the M1 chip for graphics.

The A18 Pro chip lacks Thunderbolt support, so the new MacBook would likely be equipped with regular USB-C ports. The current 13-inch MacBook Air starts at $999 in the U.S., so the new MacBook would likely have a starting price of between $699 and $899. The more-affordable MacBook could also come in some fun new colors like Silver, Blue, Pink, and Yellow.

MacBook Pro With M5 Pro and M5 Max


Apple is going to refresh the rest of the MacBook Pro lineup with M5 Pro and M5 Max chips in early 2026, having already updated its base 14-inch MacBook Pro with a standard M5 chip in October. The M5 series is based on TSMC's third-generation 3-nanometer technology. Based on improvements to the base MacBook Pro with M5 chip, faster SSD performance and higher memory bandwith are also likely for the high-end models. No other major changes are expected, with Apple holding over a completely refreshed design until the M6 models.

If Apple retains current pricing levels, the 14-inch MacBook Pro with M5 Pro chip will start at $1,999, while the 16-inch model with M5 Pro chip will start at $2,399. For the M5 Max equivalents, prices could start at $3,199 for the 14-inch model, and $3,499 for the 16-inch machine.

M5 MacBook Air


While the M4 MacBook Air model isn't exactly old, attention is already turning to its successor. The M5 series is reportedly being manufactured using TSMC's advanced 3-nanometer process technology, and we have some idea of what to expect in terms of performance, thanks to the recently released M5 iPad Pro: benchmarks show single-core scores around 4,133 and multi-core scores around 15,437. That's roughly a 12-15% jump over the M4 iPad Pro in both categories. As for graphics performance, the M5 chip appears to have up to a 36% faster GPU compared to the M4 chip.

The benchmark suggests Apple has focused on modest clock speed increases and core-level efficiency improvements for the M5 chip, rather than an architecture overhaul. In other words, the M5 will be similar to the step-wise performance upgrade from M3 to M4. Expect 10-15% faster CPU speeds, a slightly more powerful GPU, and better efficiency, potentially leading to even longer battery life.

Bloomberg's Mark Gurman reports that Apple plans to roll out M5 versions of the MacBook Air in the first quarter of this year. Based on previous spring refreshes, this suggests a likely March 2026 window. As for pricing, we expect it to remain stable, with the base model sticking with the current entry-level $999 price.

MacBook Pro With Touchscreen OLED Display


Apple is reportedly developing a completely new version of the MacBook Pro packed with next-generation hardware features. The redesigned models are expected to boast M6 chips, which could adopt a completely new packaging based on TSMC's 2nm process that allows components such as the CPU, GPUs, DRAM, and Neural Engine to be more tightly integrated.

Bloomberg's Mark Gurman says Apple is readying OLED technology for these models. Compared to current MacBook Pro models that use mini-LED screens, the benefits of OLED technology would include increased brightness, higher contrast ratio with deeper blacks, improved power efficiency for longer battery life, and more. In addition, Gurman reports that the new machines will also have "thinner and lighter frames." Apple is apparently focusing on delivering the thinnest possible device without compromising on battery life or major new features.

The redesigned 14-inch and 16-inch MacBook Pro models are also expected to have a hole-punch camera at the top of the display, rather than the notch we've become accustomed to. Gurman says that the design "leaves a display area around the sensor... similar in concept to the Dynamic Island on the iPhone."

Apple's first OLED MacBook Pro will also feature a touchscreen display, according to analyst Ming-Chi Kuo. The claim has since been corroborated by Gurman, noting that the touchscreen MacBook Pro will retain a full trackpad and keyboard.

Research firm Omdia says Apple is "highly likely" to introduce new MacBook Pros featuring OLED displays this year, while Gurman has said the new OLED machines are being readied for late 2026 or early 2027. It would be unusual for Apple to introduce two ‌MacBook Pro‌ refreshes in the same year, but there is precedent for it: Apple updated the MacBook Pro lineup twice in 2023, first with M2 Pro/M2 Max chips in January and then with M3/M3 Pro/M3 Max chips in late October.

Due to the pricier components, the new 14-inch and 16-inch MacBook Pros are expected to cost a few hundred dollars more than current versions. Today's models with high-end chips start at $1,999 for the 14-inch version and $2,499 for the 16-inch one.Related Roundups: MacBook Air, MacBook ProBuyer's Guide: 15" MacBook Air (Caution), MacBook Pro (Caution), 13" MacBook Air (Caution)Related Forums: MacBook Air, MacBook Pro
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Security Is a Developer Experience Problem, Rooted in Our Foundations

For more than a decade, the industry has tried to improve software security by pushing it closer to developers. We moved scanners into CI, added security checks to pull requests, and asked teams to respond faster to an ever-growing stream of vulnerabilities. And yet, the underlying problems have not gone away.
The issue is not that developers care too little about security. It is that we keep trying to fix security at the edges, instead of fixing the foundations. Hardened container images change that dynamic by reducing attack surface and eliminating much of the low-signal security noise before it ever reaches development teams.
Security Fails When It Becomes Noise
Most developers I know care deeply about building secure software. What they do not care about is security theater.
The way we handle security issues today, especially CVEs, often creates a steady stream of low-signal work for development teams. Alerts fire constantly. Many are technically valid but practically irrelevant. Others ask developers to patch components they did not choose and do not meaningfully control. Over time, this turns security into background noise.
When that happens, the system has already failed. Developers are forced to context switch, teams burn time debating severity scores, and real risk gets buried alongside issues that do not matter. This is not a motivation problem. It is a system design problem.
The industry responded by trying to “shift left” and push security earlier in the development cycle. In practice, this often meant pushing more work onto developers without giving them better defaults or foundations. The result was more toil, more alerts, and more reasons to tune it all out.
Shifting left was the right instinct but the wrong execution. The goal should not be making developers do more security work. It should be making secure choices the painless, obvious default so developers do less security work while achieving better outcomes.
Why Large Images Were the Default
To understand how we got here, it helps to be honest about why most teams start with large, generic base images.
When Docker launched in 2013, containers were unfamiliar. Developers reached for what they knew: full Linux distributions and familiar Debian or Ubuntu environments with all the debugging tools they relied on. 
Large images that had everything were a rational default. This approach optimized for ease and flexibility. When everything you might ever need is already present, development friction goes down. Builds fail less often. Debugging is simpler. Unknown dependencies are less likely to surprise you at the worst possible time.
For a long time, doing something more secure has required real investment. Teams needed a platform group that could design, harden, and continuously maintain custom base images. That work had to compete with product features and infrastructure priorities. Most organizations never made that tradeoff, and that decision was understandable.
So the industry converged on a familiar pattern. Start with a big image. Ship faster in the short term. Deal with the consequences later.
Those consequences compound. Large images dramatically increase the attack surface. They accumulate stale dependencies. They generate endless CVEs that developers are asked to triage long after the original choice was made. What began as a convenience slowly turns into persistent security and operational drag that slows development velocity and software shipments.
Secure Foundations Can Improve Developer Experience
There is a widely held belief that better security requires worse developer experience. In practice, the opposite is often true.
Starting from a secure, purpose-built foundation, like Docker Hardened Images, reduces complexity rather than adding to it. Smaller images contain fewer packages, which means fewer vulnerabilities and fewer alerts. Developers spend less time chasing low-impact CVEs and more time building actual product.
The key is that security is built into the foundation itself. Image contents are explicit and reproducible. Supply chain metadata like signatures, SBOMs, and provenance are part of the image by default, not additional steps developers have to wire together themselves. At the same time, these foundations are easy to customize securely. Teams can extend or tweak their images without undoing the hardening, thanks to predictable layering and supported customization patterns. This eliminates entire categories of hidden dependencies and security toil that would otherwise fall on individual teams.
There are also tangible performance benefits. Smaller images pull faster, build faster, and deploy faster. In larger environments, these gains add up quickly.
Importantly, this does not require sacrificing flexibility. Developers can still use rich build environments and familiar tools, while shipping minimal, hardened runtime images into production.
This is one of the rare cases where improving security directly improves developer experience. The tradeoff we have accepted for years is not inevitable.
What Changes When Secure Foundations Are the Default
When secure foundations and hardened images become the default starting point, the system behaves differently. Developers keep using the same Docker workflows they already know. The difference is the base they start from. 
Security hardening, patching, and supply chain hygiene are handled once in the foundation instead of repeatedly in every service. Secure foundations are not limited to operating system base images. The same principles apply to the software teams actually build on top of, such as databases, runtimes, and common services. Starting from a hardened MySQL or application image removes an entire class of security and maintenance work before a single line of application code is written.
This is the problem Docker Hardened Images are designed to address. The same hardening principles are applied consistently across widely used open source container images, not just at the operating system layer, so teams can start from secure defaults wherever their applications actually begin. The goal is not to introduce another security workflow or tool. It is to give developers better building blocks from day one.
Because the foundation is maintained by experts, teams see fewer interruptions. Fewer emergency rebuilds. Fewer organization-wide scrambles when a widely exploited vulnerability appears. Security teams can focus on adoption and posture instead of asking dozens of teams to solve the same problem independently.
The result is less security toil and more time spent on product work. That is a win for developers, security teams, and the business.
Build on Better Defaults
For years, we have tried to improve security by asking developers to do more. Patch faster. Respond to more alerts. Learn more tools. That approach does not scale.
Security scales when defaults are strong. When foundations are designed to be secure and maintained over time. When developers are not forced to constantly compensate for decisions that were made far below their code.
If we want better security outcomes without slowing teams down, we should start where software actually starts. That requires secure foundations, like hardened images, that are safe by default. With better foundations, security becomes quieter, development becomes smoother, and the entire system works the way it should.
That is the bar we should be aiming for.
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Best Apple Deals of the Week: Save on Anker's Newest Nano Chargers, Plus Steep Discounts on M5 MacBook Pro and More

We tracked big discounts during the first full week of 2026, including a new record low price on the Apple Pencil Pro and pre-order discounts on Anker's just-announced collection of Nano chargers. Below you'll also find solid discounts on iPad mini 7, AirPods 4, and M5 MacBook Pro.

Note: MacRumors is an affiliate partner with some of these vendors. When you click a link and make a purchase, we may receive a small payment, which helps us keep the site running.

Anker


What's the deal? Save on Anker's newest Nano chargers and more
Where can I get it? Anker
Where can I find the original deal? Right here
$10 OFFAnker 45W Nano Charger for $29.99
$40 OFFAnker Nano Docking Station for $109.69

Anker announced a new series of products at CES this week, and most of them will begin rolling out to customers later in January. A few of these devices, including the Nano Docking Station and 45W Nano Charger, have pre-order discounts on Anker's website, and we're also tracking big discounts in Anker's New Year's sale.

Apple Pencil Pro


What's the deal? Take $35 off Apple Pencil Pro
Where can I get it? Amazon
Where can I find the original deal? Right here
$35 OFFApple Pencil Pro for $92.97

Apple Pencil Pro is available for its all-time low price of $92.97 this week on Amazon, down from $129.00. This beats the price we tracked over the holiday season by about $2, and right now it's only available on Amazon.

iPad Mini 7


What's the deal? Take up to $109 off iPad mini 7
Where can I get it? Amazon
Where can I find the original deal? Right here
$109 OFF128GB Wi-Fi iPad mini 7 for $389.99
$100 OFF256GB Wi-Fi iPad mini 7 for $499.00
$100 OFF512GB Wi-Fi iPad mini 7 for $699.00

Amazon and Best Buy have a few discounts on the iPad mini 7 for the New Year, starting at $389.99 for the 128GB Wi-Fi tablet, down from $499.00. You'll also find a few deals on cellular models during this sale.

AirPods 4


What's the deal? Take up to $99 off AirPods Max and AirPods 4
Where can I get it? Amazon
Where can I find the original deal? Right here
$29 OFFAirPods 4 for $99.99
$99 OFFAirPods Max for $449.99

This week we tracked a few AirPods deals, including $29 off AirPods 4 and $99 off AirPods Max. Both of these are solid second-best prices on each model, and we haven't seen best-ever prices on these yet in 2026.

M5 MacBook Pro


What's the deal? Take up to $199 of M5 MacBook Pro
Where can I get it? Amazon
Where can I find the original deal? Right here
$150 OFF14-inch M5 MacBook Pro (16GB RAM/512GB) for $1,449.00
$199 OFF14-inch M5 MacBook Pro (16GB RAM/1TB) for $1,599.99

Amazon this week dropped the price of the new M5 MacBook Pro to $1,449.00, down from $1,599.00. This is the 10-Core model with 16GB RAM and 512GB SSD, and it's a solid second-best price on the M5 MacBook Pro.

If you're on the hunt for more discounts, be sure to visit our Apple Deals roundup where we recap the best Apple-related bargains of the past week.



Deals Newsletter

Interested in hearing more about the best deals you can find in 2026? Sign up for our Deals Newsletter and we'll keep you updated so you don't miss the biggest deals of the season!




Related Roundup: Apple Deals
This article, "Best Apple Deals of the Week: Save on Anker's Newest Nano Chargers, Plus Steep Discounts on M5 MacBook Pro and More" first appeared on MacRumors.com

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Russian APT28 Runs Credential-Stealing Campaign Targeting Energy and Policy Organizations

Russian state-sponsored threat actors have been linked to a fresh set of credential harvesting attacks targeting individuals associated with a Turkish energy and nuclear research agency, as well as staff affiliated with a European think tank and organizations in North Macedonia and Uzbekistan. The activity has been attributed to APT28 (aka BlueDelta), which was attributed to a "sustained"View the full article
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Build Scalable Web Apps Using AngularJS and NodeJS

Introduction: Problem, Context & Outcome
Developers today face increasing pressure to deliver dynamic, scalable web applications efficiently. Fragmented workflows between frontend and backend, slow updates, and maintenance challenges can delay projects and reduce quality. The Master in JavaScript with AngularJS and NodeJS program addresses these challenges by equipping learners with end-to-end full-stack development skills. Participants learn to build interactive AngularJS frontends, develop scalable NodeJS backends, and integrate them seamlessly for production-ready applications. This program also includes hands-on projects, CI/CD integration, and cloud deployment best practices. Completing the course enables developers to deliver enterprise-grade applications faster and with higher reliability.
Why this matters: Full-stack JavaScript expertise reduces operational complexity, accelerates delivery, and ensures maintainable web applications.
What Is Master in JavaScript with AngularJS and NodeJS?
This program is designed for full-stack web development using modern JavaScript technologies. AngularJS provides a framework to create interactive single-page applications (SPAs) with reusable components and two-way data binding. NodeJS offers an event-driven, non-blocking runtime for backend services, enabling high concurrency and fast response times. Learners gain practical experience in building RESTful APIs, connecting to databases, and deploying applications using DevOps-aligned CI/CD pipelines. By mastering this stack, developers can handle both frontend and backend logic in a single language, making development more efficient and consistent.
Why this matters: Mastering AngularJS and NodeJS ensures developers can deliver fully integrated applications that are scalable, maintainable, and enterprise-ready.
Why Master in JavaScript with AngularJS and NodeJS Is Important in Modern DevOps & Software Delivery
AngularJS and NodeJS are widely adopted in enterprise web development due to their performance, scalability, and flexibility. AngularJS enables responsive, dynamic user interfaces, while NodeJS allows backend services to handle multiple concurrent requests efficiently. This combination supports DevOps practices such as automated CI/CD pipelines, microservices architectures, and cloud-native deployments. Organizations adopting this stack benefit from faster feature releases, higher application performance, and simplified maintenance. Agile teams can iterate quickly while ensuring production-ready quality.
Why this matters: Learning this stack aligns developers with modern DevOps workflows and enables faster, reliable software delivery.
Core Concepts & Key Components
JavaScript Fundamentals
Purpose: Establish a solid foundation for full-stack development.
How it works: JavaScript manages frontend interactions, asynchronous operations, and server-side logic.
Where it is used: Frontend applications, backend APIs, and full-stack solutions.
AngularJS Framework
Purpose: Create dynamic and interactive SPAs.
How it works: Uses data binding, directives, and reusable components for maintainable and modular architecture.
Where it is used: Enterprise dashboards, e-commerce platforms, and interactive web applications.
NodeJS Runtime
Purpose: Develop high-performance backend services.
How it works: Non-blocking, event-driven architecture efficiently handles multiple concurrent requests.
Where it is used: REST APIs, real-time apps, and server-side processing.
RESTful API Development
Purpose: Facilitate communication between frontend and backend.
How it works: Provides HTTP-based endpoints to send and receive structured data.
Where it is used: Mobile apps, web services, and microservices.
Database Integration
Purpose: Store and manage application data efficiently.
How it works: NodeJS interacts with databases like MongoDB or MySQL for CRUD operations.
Where it is used: Persistent storage, analytics, and transactional applications.
DevOps & Cloud Integration
Purpose: Automate deployment and manage scalable infrastructure.
How it works: Integrates with CI/CD pipelines, containerization, and orchestration tools like Docker and Kubernetes.
Where it is used: Production cloud environments and enterprise-scale deployments.
Why this matters: Understanding these concepts ensures robust, scalable, and maintainable web applications.
How Master in JavaScript with AngularJS and NodeJS Works (Step-by-Step Workflow)
Requirement Analysis: Gather project goals and user requirements. Frontend Development: Build AngularJS components for dynamic SPAs. Backend Development: Develop NodeJS RESTful APIs and server-side logic. Database Integration: Connect databases for persistent data storage. Testing: Conduct unit, integration, and functional testing. Deployment: Implement CI/CD pipelines for automated deployments. Monitoring & Optimization: Monitor application performance, logs, and optimize code.
Why this matters: This workflow mirrors professional full-stack development processes and DevOps practices. Real-World Use Cases & Scenarios
E-commerce Applications: Interactive product catalogs, checkout systems, and user dashboards. Healthcare Applications: Patient management, appointment scheduling, and telemedicine platforms. Social Media Platforms: Real-time messaging, notifications, and dynamic feeds. Enterprise SaaS Solutions: Collaboration tools, reporting dashboards, and microservices-based applications. Team roles include frontend developers (AngularJS), backend developers (NodeJS), DevOps engineers (CI/CD and cloud deployment), QA engineers (testing), and cloud engineers (production deployments). This collaboration enhances scalability, performance, and reliability.
Why this matters: Demonstrates the practical application of full-stack JavaScript in enterprise environments.
Benefits of Using Master in JavaScript with AngularJS and NodeJS
Productivity: Unified JavaScript stack accelerates development. Reliability: Structured frameworks improve code maintainability. Scalability: NodeJS handles high concurrency; AngularJS supports dynamic SPAs. Collaboration: Shared language fosters better team communication.
Why this matters: Increases efficiency, reduces errors, and improves software delivery speed. Challenges, Risks & Common Mistakes
Common errors include poorly structured AngularJS components, mishandled asynchronous NodeJS logic, and insecure APIs. Operational risks involve scaling challenges, inefficient database queries, and unstable deployments. Mitigation strategies include modular architecture, CI/CD automation, proper error handling, and continuous monitoring.
Why this matters: Prevents production issues and ensures secure, scalable applications.
Comparison Table
FeatureAngularJS + NodeJSTraditional StackLanguageSingle-language JavaScriptMultiple languagesScalabilityHighModerateFrontend InteractivityDynamic SPAsStatic pagesBackend PerformanceEvent-drivenBlocking I/OCI/CD SupportStrongLimitedDeploymentAutomatedManualCloud CompatibilityExcellentModerateModularityHighLowIndustry AdoptionGrowingDecliningMaintainabilityEasyModerateWhy this matters: Illustrates why this stack is suitable for modern web development. Best Practices & Expert Recommendations
Use modular AngularJS components for maintainable frontends. Follow proper asynchronous patterns in NodeJS. Implement automated CI/CD pipelines. Monitor application performance and logs. Apply database and API security best practices.
Why this matters: Ensures production-ready, secure, and maintainable applications. Who Should Learn or Use Master in JavaScript with AngularJS and NodeJS?
This program is ideal for frontend developers, backend developers, DevOps engineers, QA specialists, SREs, and cloud engineers. Beginners gain foundational knowledge, while experienced professionals can refine full-stack skills. The program is relevant for professionals building modern web applications in both startups and large enterprises.
Why this matters: Aligns learning with practical roles and career advancement opportunities.
FAQs – People Also Ask
What is Master in JavaScript with AngularJS and NodeJS?
A full-stack program teaching AngularJS frontend and NodeJS backend development.
Why this matters: Builds enterprise-ready web development skills.
Why combine AngularJS with NodeJS?
AngularJS handles frontend UIs; NodeJS manages backend efficiently.
Why this matters: Enables seamless full-stack application development.
Is it suitable for beginners?
Yes, the course covers fundamentals and hands-on projects.
Why this matters: Accessible for all skill levels.
Can it handle high-traffic applications?
Yes, NodeJS supports scalable asynchronous processing.
Why this matters: Ideal for enterprise-grade applications.
Does it integrate with CI/CD pipelines?
Yes, it supports automated deployment workflows.
Why this matters: Follows DevOps-aligned practices.
Is it cloud-ready?
Yes, compatible with Docker, Kubernetes, and cloud platforms.
Why this matters: Ensures scalable and maintainable deployments.
How does it compare with traditional stacks?
Faster development, unified language, and better scalability.
Why this matters: Reduces operational complexity.
Which industries use this stack?
E-commerce, healthcare, SaaS, social media.
Why this matters: Shows real-world relevance.
Can beginners deploy production-ready apps?
Yes, hands-on exercises cover CI/CD deployment.
Why this matters: Builds practical experience.
Where can I learn this professionally?
At DevOpsSchool.
Why this matters: Offers structured, enterprise-aligned training.
Branding & Authority
This program is offered by DevOpsSchool, a trusted global platform. Mentorship is provided by Rajesh Kumar, who has 20+ years of expertise in DevOps & DevSecOps, SRE, DataOps, AIOps & MLOps, Kubernetes & Cloud Platforms, and CI/CD & Automation.
Why this matters: Learners gain guidance from industry veterans with real-world experience.
Call to Action & Contact Information
Enroll here:
Master in JavaScript with AngularJS and NodeJS
Email: [email protected]
Phone & WhatsApp (India): +91 7004215841
Phone & WhatsApp (USA): +1 (469) 756-6329


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Get Your iPhone to Ask Callers Who They Are Before You Answer

Spam and cold calls have become such a nuisance that many people simply don't answer their phone unless they recognize the number. In iOS 26, though, you can learn about who's calling before you respond, thanks to a clever feature that intercepts unknown calls and asks the caller to identify themselves before your iPhone even rings.


The "Ask Reason for Calling" feature is kind of like having your own receptionist. When someone who isn't in your Contacts calls, your iPhone automatically answers the call with a polite automated message asking for their name and reason for calling. The caller is placed on hold while their response is transcribed to text and displayed on your screen, letting you decide whether to accept, decline, or ask for more information.

It's a decent upgrade from the existing "Silence Unknown Callers" option, which simply sends all unrecognized numbers straight to voicemail. With the new approach, legitimate callers – like your doctor or a delivery service – can identify themselves, whereas robocallers and spammers are likely to hang up when greeted by the automated response.

How to Enable Ask Reason for Calling

The following steps show you how to turn on the feature:

Open Settings on your iPhone.
Scroll down and tap Apps.
Select Phone.
Under the "Screen Unknown Callers" section, tap Ask Reason for Calling.


That's all there is to it. Your iPhone will now intercept calls from numbers not saved in your Contacts and request information before alerting you.

Other Unknown Caller Screening Options

If you don't want to use the new Ask Reason for Calling feature, iOS 26 offers two alternative approaches for handling unknown numbers:

Silence: This option automatically sends all calls from unsaved numbers to voicemail. The calls still appear in your Recents list, and you'll receive the voicemail if the caller leaves one. It's the same behavior as the "Silence Unknown Callers" toggle in iOS 18.

Never: With this setting, calls from unknown numbers ring normally, just like calls from saved contacts. Missed calls appear in your Recents list as usual. It's your typical iPhone calling experience.

To switch between these options, go to Settings ➝ Apps ➝ Phone, and select your preferred option under "Screen Unknown Callers."

The Ask Reason for Calling feature works best when you maintain an up-to-date Contacts list. Any number saved in Contacts will ring through normally without triggering the screening process, so make sure to add the details of legitimate contacts as soon as you know them.
This article, "Get Your iPhone to Ask Callers Who They Are Before You Answer" first appeared on MacRumors.com

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Ni8mare: Kritische n8n-Lücke bedroht 100.000 Server

jittawit21 – shutterstock.com
Forscher des Security-Anbieters Cyera haben eine schwerwiegende Schwachstelle in der Workflow-Automatisierungsplattform n8n entdeckt. Sie ermöglicht es Angreifern, beliebigen Code auszuführen. Auf diese Weise könnten sie die vollständige Kontrolle über die betroffene Umgebung übernehmen, so die Experten.
Schwerwiegende Folgen
Laut Forschungsbericht sind davon 100.000 Server betroffen. Die Sicherheitslücke wird mit dem höchsten CVSS-Wert von 10,0 eingestuft und ist als CVE-2026-21858 gekennzeichnet. Die Security-Spezialisten warnen, dass die Lücke massive Auswirkungen hat.
Bei n8n handelt es sich um ein weitverbreitetes Open-Source-Automatisierungs-Tool. Es wird von vielen Unternehmen eingesetzt, um Chat-Apps, Formulare, Cloud-Speicher, Datenbanken und APIs von Drittanbietern miteinander zu verknüpfen. Wie auf der NPM-Datenbank zu sehen ist, kommt das dazugehörige Paket aktuell auf rund 60.000 Downloads pro Woche.
Auf vielen n8n-Systemen seien etwa Informationen zu finden, die Zugriffe auf unternehmensinterne Daten bei Google Drive, Salesforce oder Zahlungsdiensten ermöglichten, ebenso wie API-Keys, OAuth-Token, Kundendaten, CI/CD-Pipelines, erklären die Cyera-Forscher.
So funktioniert der Angriff
Den Sicherheitsexperten zufolge liegt die Ursache des Sicherheitsproblems darin, wie n8n Webhooks verarbeitet. Dabei werden Workflows gestartet, wenn Daten aus externen Systemen wie Webformularen, Messaging-Plattformen oder Benachrichtigungsdiensten eintreffen. Durch Ausnutzen eines sogenannten „Content-Type Confusion”-Fehlers können Angreifer HTTP-Header manipulieren und interne Variablen überschreiben, die von der Anwendung verwendet werden. Dies ermöglicht es, beliebige Dateien aus dem zugrunde liegenden System zu lesen und eine RCE-Attacke (Remote-Code-Execution) zu starten.
Die Forscher demonstrieren den Angriff, den sie als Ni8mare bezeichnen, am Beispiel einer Wissensdatenbank, die sich mit Datei-Uploads befüllen lässt. Demnach können Angreifer die Lücke nutzen, um Zugangsdaten hineinzukopieren und sich anschließend Admin-Zugriff verschaffen.
Nach eigenen Angaben hat Cyera die Entwickler von n8n bereits im November 2025 über die Schwachstelle informiert. Daraufhin wurde mit Version 1.121.0 ein Patch bereitgestellt.

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CSOonline

Squinting Face, Pickle, and Lighthouse Among New Emoji Coming to iOS

The Unicode Consortium has published a draft list of emoji that could come to smartphones and other devices in the future. The list shared by Emojipedia outlines 19 emoji candidates under consideration for Emoji 18.0, which is expected to be finalized in September 2026.


Among the proposed additions are a squinting face emoji, left- and right-pointing thumb gestures, a pickle, a lighthouse, a meteor, an eraser, and a net with a handle. The draft list also includes a monarch butterfly emoji, providing a more specific alternative to the existing generic butterfly.

Along with the 9 new emoji concepts, Emoji 18.0 would (if approved as currently proposed) add 10 additional skin tone variants tied to two of the base emoji. This would bring the total number of recommended emoji characters close to 4,000.

Emojipedia has shared sample artwork for many of the candidates, but Apple designers will need to create their own version of each character in the Apple style if the emoji are ultimately approved. As with previous draft lists, the proposed lineup is not final and may change during Unicode's review process.

Apple will need to roll out its own versions of the new emoji through software updates, so the new characters would likely arrive on iPhone in late 2026 or early 2027, as part of iOS 27.

Apple has consistently adopted new Unicode emoji in past software releases, and previously announced Unicode 17 additions are expected to come to Apple devices with the release of iOS 26.4, iPadOS 26.4, macOS 26.4, watchOS 26.4, and visionOS 26.4 in March or April this year. Tag: Emoji
This article, "Squinting Face, Pickle, and Lighthouse Among New Emoji Coming to iOS" first appeared on MacRumors.com

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CrowdStrike to acquire SGNL for $740M, expanding real-time identity security

CrowdStrike will pay $740 million to acquire identity security startup SGNL, adding real-time authorization capabilities that grant and revoke access based on current risk conditions rather than static permissions.
The deal, expected to close in CrowdStrike’s fiscal first quarter ending April 30, will be paid mostly in cash with some stock subject to vesting, CrowdStrike said in a statement.
SGNL’s technology sits between identity providers and resources, evaluating access requests using contextual data, including user behavior, device posture, and threat intelligence.
The acquisition reflects growing concern about non-human identities such as service accounts, API keys, and AI agents that operate with broad permissions across cloud environments. Machine identities now outnumber human identities by as much as 82 to 1 in some environments, according to industry estimates cited by Gartner.
“AI agents operate with superhuman speed and access, making every agent a privileged identity that must be protected,” CrowdStrike CEO George Kurtz said in the statement.
Filling a capability gap
CrowdStrike is adding SGNL’s capabilities to address this risk. The technology works with existing identity systems from Okta, Microsoft, and AWS rather than replacing them.
“This isn’t just consolidation — it fills a real gap in dynamic, risk-aware authorization,” said Meng Liu, senior analyst at Forrester. “As AI agents and insider threats rise, static IAM is no longer enough.”
The approach differs from traditional identity and access management, which typically authenticates users at login and relies on periodic access reviews. SGNL evaluates access continuously, revoking privileges immediately when conditions change. For instance, if CrowdStrike’s Falcon platform detects suspicious endpoint activity.
“SGNL offers continuous, contextual authorization that can make split-second decisions based on real-time signals, something traditional IAM systems have struggled with,” said Apeksha Kaushik, principal analyst at Gartner. Gartner predicts that by 2028, 25% of enterprise breaches will be traced to AI agent abuse from both external and malicious internal actors.
Analysts argue that the acquisition will not make CrowdStrike a competitor for IAM platforms. “This fills a specific capability gap around real-time identity threat detection and enforcement, an area where traditional IAM platforms are comparatively static,” said Arjun Chauhan, practice director at Everest Group. “Microsoft and Okta primarily own identity lifecycle management, authentication, and access governance.”
Market consolidation accelerates
The $740 million price reflects broader consolidation as cybersecurity vendors race to expand identity capabilities. The deal marks the latest in a wave of identity security acquisitions as platform vendors expand beyond core products. Liu compared the move to Palo Alto Networks’ acquisition of CyberArk in 2025, noting both vendors are racing to combine detection and enforcement into a single platform.
“Identity has become the center of gravity in cybersecurity,” said John Paul Cunningham, CISO at Silverfort. “We’re seeing clear segmentation emerge: pure identity security players, hybrid vendors trying to bolt identity into existing products, and large platform companies like Palo Alto Networks and now CrowdStrike expanding as part of broader security ecosystems.”
The identity security market is expected to grow from approximately $29 billion in 2025 to $56 billion by 2029, according to IDC data cited by CrowdStrike. The $740 million price follows Okta’s $6.5 billion purchase of Auth0 in 2021 and Thoma Bravo’s $2.3 billion take-private of ForgeRock in 2023.
SGNL was founded by former Google employees and raised approximately $75 million from Costanoa Ventures and CRV before the acquisition.
Enterprise adoption questions
Whether continuous authorization becomes standard practice depends partly on how rapidly non-human identities proliferate. “The urgency is real, but uneven across enterprises,” Chauhan said. “In client conversations, we increasingly see interest in adaptive and continuous authorization, especially in regulated industries, digital-native enterprises, and organizations with high levels of third-party or machine identity access.”
Most enterprises are not replacing traditional IAM. “Instead, they are layering real-time controls on top of existing IAM to address gaps around insider risk, session-level anomalies, and post-authentication compromise,” Chauhan said.
The practical challenge is defining policies that adapt to dynamic conditions. Unlike role-based access control, continuous authorization requires organizations to establish baseline behavior patterns and acceptable risk thresholds.
Integration details remain unclear. CrowdStrike has not disclosed when SGNL capabilities will be available to Falcon customers, whether they require additional licensing, or what changes to existing IAM configurations may be necessary.
The acquisition is part of CrowdStrike’s platform expansion spree following the July 2024 software update incident that caused widespread Windows system outages. The company reported fiscal third-quarter annual recurring revenue of $4 billion in December, up 25% year-over-year.
“This should primarily be viewed as long-term platform expansion rather than a short-term recovery signal,” Chauhan said. “CrowdStrike has been steadily positioning itself as a broader cybersecurity platform for several years. The acquisition reinforces that trajectory and helps reduce overreliance on endpoint security alone.”
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Python with Machine Learning: Step-by-Step Guide for Production ML

Introduction: Problem, Context & Outcome
Engineering teams increasingly need to deliver intelligent software, yet many struggle to transform machine learning ideas into reliable production systems. Data experiments succeed in isolation, but deployments fail due to weak pipelines, unclear ownership, and limited operational maturity. Meanwhile, organizations demand faster outcomes from AI investments across products, platforms, and automation workflows. As machine learning becomes a core capability rather than an experiment, teams need a stable, flexible, and widely supported foundation. Python with Machine Learning provides that foundation by combining developer productivity with production readiness. This guide explains how Python supports the full machine learning lifecycle, how teams integrate it into DevOps and cloud workflows, and what professionals gain by mastering it. Why this matters: Strong foundations turn AI initiatives into deliverable business outcomes.
What Is Python with Machine Learning?
Python with Machine Learning refers to using Python as the primary language for building, training, deploying, and maintaining machine learning systems. Python offers readable syntax, rich libraries, and a mature ecosystem that supports data processing, modeling, and production deployment. Developers use Python to explore data, experiment with algorithms, and validate results quickly. DevOps and platform teams use Python to automate pipelines, package models, and deploy services to cloud environments. Python enables teams to use the same language across experimentation and production, reducing friction and handoff issues. Organizations adopt Python because it balances simplicity with enterprise scalability. Why this matters: A shared language across teams improves speed and reliability.
Why Python with Machine Learning Is Important in Modern DevOps & Software Delivery
Modern software delivery increasingly depends on intelligence embedded directly into applications. CI/CD pipelines now deploy models alongside code. Agile teams iterate on predictions, recommendations, and automation features continuously. Python with Machine Learning aligns naturally with DevOps because it integrates easily with version control, testing frameworks, automation tools, and cloud platforms. Python supports repeatable training, automated validation, and controlled deployments across environments. Enterprises standardize on Python to reduce operational risk while scaling AI initiatives safely. Why this matters: Machine learning must meet the same reliability standards as production software.
Core Concepts & Key Components
Data Collection and Preparation
Purpose: Transform raw data into usable inputs.
How it works: Python libraries clean, normalize, and analyze datasets.
Where it is used: Data pipelines and ML workflows.
Why this matters: Data quality directly affects model performance.
Feature Engineering
Purpose: Improve how models learn from data.
How it works: Python converts raw variables into meaningful features.
Where it is used: Model experimentation and training.
Why this matters: Strong features improve prediction accuracy.
Machine Learning Algorithms
Purpose: Learn patterns and relationships.
How it works: Algorithms train on historical data.
Where it is used: Classification, prediction, and recommendation systems.
Why this matters: Algorithms drive intelligent behavior.
Model Training and Evaluation
Purpose: Validate performance and robustness.
How it works: Python measures accuracy, bias, and error metrics.
Where it is used: Development and testing stages.
Why this matters: Evaluation prevents unreliable predictions.
Deployment and Automation
Purpose: Deliver models to real users.
How it works: Python packages models as APIs or services.
Where it is used: Cloud platforms and CI/CD pipelines.
Why this matters: Models must operate safely in production.
Why this matters: These components cover the complete machine learning lifecycle.
How Python with Machine Learning Works (Step-by-Step Workflow)
The workflow begins with identifying business objectives and data sources. Teams collect and preprocess data using Python tools. Engineers design features and select suitable algorithms. Models train and undergo evaluation and validation. Approved models package into deployable artifacts. DevOps pipelines release models to cloud or container platforms. Monitoring tracks accuracy, drift, and performance over time. Retraining workflows activate when data patterns change. This workflow mirrors real DevOps lifecycles and enables continuous improvement. Why this matters: Structured workflows reduce production failures and rework.
Real-World Use Cases & Scenarios
Organizations use Python with Machine Learning for fraud detection, demand forecasting, personalization, predictive maintenance, and automation. Developers embed predictions into applications and APIs. DevOps engineers manage training and deployment pipelines. QA teams validate outputs and edge cases. SRE teams monitor reliability and performance. Cloud teams scale infrastructure dynamically to match demand. These cross-functional efforts deliver measurable business results across industries. Why this matters: Real-world usage proves enterprise readiness.
Benefits of Using Python with Machine Learning
Organizations gain a unified ecosystem for AI development and deployment. Teams innovate faster without sacrificing control or reliability.
Productivity: Rapid experimentation and iteration Reliability: Mature libraries and testing support Scalability: Cloud-native deployment options Collaboration: One language across teams Why this matters: Benefits multiply as AI adoption increases.
Challenges, Risks & Common Mistakes
Teams often underestimate data governance challenges. Beginners misuse algorithms without proper validation. Weak deployment practices create fragile systems. Lack of monitoring leads to silent failures. Teams mitigate these risks through automation, validation, and observability practices. Why this matters: Awareness prevents costly production incidents.
Comparison Table
Traditional SoftwarePython with Machine LearningRule-based logicData-driven modelsStatic behaviorAdaptive systemsManual decisionsPredictive insightsLimited automationAutomated pipelinesSiloed teamsCross-functional collaborationSlow experimentationRapid iterationHard to scaleCloud-readyMinimal monitoringContinuous monitoringReactive fixesProactive improvementLimited insightIntelligent prediction Why this matters: Comparison highlights the shift toward intelligent systems.
Best Practices & Expert Recommendations
Teams should standardize data pipelines early. Version control must track data and models. Automation should manage training and deployment. Monitoring should detect drift and bias continuously. Documentation must remain current and accessible. Why this matters: Best practices ensure sustainable machine learning systems.
Who Should Learn or Use Python with Machine Learning?
Developers building intelligent features gain immediate value. DevOps engineers support deployment and automation workflows. Cloud, SRE, and QA professionals ensure reliability and scalability. Beginners gain an accessible entry point, while experienced teams scale advanced solutions. Why this matters: Broad adoption increases organizational impact.
FAQs – People Also Ask
What is Python with Machine Learning?
It uses Python to build ML systems across lifecycles. Why this matters: Clear understanding speeds adoption.
Is Python beginner-friendly for ML?
Yes, syntax stays simple and libraries abstract complexity. Why this matters: Accessibility drives learning.
Is it enterprise-ready?
Yes, many enterprises standardize on Python. Why this matters: Industry trust matters.
Does it integrate with DevOps pipelines?
Yes, through CI/CD and automation tools. Why this matters: Production stability matters.
How does it compare with other languages?
Python balances simplicity and ecosystem strength. Why this matters: Efficiency improves outcomes.
Can models scale in production?
Yes, using cloud platforms. Why this matters: Scalability supports growth.
Is monitoring required?
Yes, to detect drift and failures. Why this matters: Reliability depends on monitoring.
Does Python support deployment?
Yes, via APIs and services. Why this matters: Models must reach users.
Is it relevant for AI careers?
Yes, global demand remains strong. Why this matters: Skills longevity matters.
Is Python future-proof for ML?
Yes, AI adoption continues expanding. Why this matters: Long-term value matters.
Branding & Authority
DevOpsSchool operates as a globally trusted learning platform delivering enterprise-grade education in DevOps, cloud computing, data engineering, and artificial intelligence. The platform emphasizes hands-on labs, real-world scenarios, and production-focused curricula designed for modern engineering teams. Enterprises and professionals rely on structured programs that bridge theory and real execution across domains. Why this matters: Trusted platforms ensure job-ready learning.
Rajesh Kumar brings more than 20 years of hands-on experience across DevOps, DevSecOps, Site Reliability Engineering, DataOps, AIOps, MLOps, Kubernetes, cloud platforms, CI/CD, and large-scale automation. His mentorship focuses on practical execution, scalability, and long-term operational reliability. Learners gain guidance grounded in real production challenges. Why this matters: Experienced mentorship accelerates mastery.
Call to Action & Contact Information
Explore structured learning through the official course page:
Python with Machine Learning
Email: [email protected]
Phone & WhatsApp (India): +91 7004215841
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CISA flags max-severity bug in HPE OneView amid active exploitation

A max-severity remote code execution (RCE) flaw in HPE’s OneView management platform has been flagged by the Cybersecurity & Infrastructure Security Agency (CISA) for active exploitation. The flaw, tracked as CVE-2025-37164, has been added to CISA’s Known Exploited Vulnerability (KEV) Catalog, days after the company disclosed it with a fix.
“The CVE-2025-37164 OneView vulnerability is severe because it allows unauthenticated remote code execution through a publicly reachable REST API endpoint,” said Chrissa Constantine, Senior Cybersecurity Solution Architect at Black Duck. “Given how central OneView is for managing servers, storage, and networking, this vulnerability doesn’t just compromise an application – it puts the entire environment at risk. This is why proactive API security assessments are non-negotiable for any system exposing management or automation interfaces.”
HPE has already released advisories and a patch addressing the issue, but enterprises are facing a narrow window to respond before a management-layer compromise turns into full-environment control.
Infrastructure-wide consequences
CVE-2025-37164 is caused by improper input handling in a publicly reachable REST API used by HPE OneView, allowing unauthenticated attackers to execute arbitrary commands on the underlying system. The flaw carries a CVSS score of 10.0, reflecting both the lack of authentication and the direct path to remote code execution, which makes opportunistic scanning and rapid exploitation far more likely.

HPE OneView acts as a single pane of glass for servers, storage, and networking, often integrated with identity systems, ticketing platforms, and automation workflows. An unauthenticated RCE in that layer gives attackers a shortcut straight into the heart of enterprise operations.

“HPW OneView’s position in the company and the vulnerability’s severity score make it bad,” Randolph Barr, chief information security officer at Cequence Security. “When hackers breach a platform such as HPE OneView, they not only gain access to a single system but also penetrate the core operations of the environment.”
Not an ‘apply and move on’ solution
While CISA’s KEV inclusion raised the priority immediately, enterprises can’t treat OneView like a routine endpoint patch. Management-plane software is often deployed on-premises, sometimes on physical servers, and tightly coupled with production workflows. A rushed fix that breaks monitoring, authentication, or integrations can be almost as dangerous as the vulnerability itself.
Barr cautioned that organizations first need to understand how OneView is deployed: whether on physical hardware, as a virtual machine with snapshot support, or in a clustered configuration, before moving to patch. Virtualized setups may allow quicker patch-and-rollback cycles, while older or large on-prem deployments demand careful sequencing and tested backout plans.

“Security teams should be collecting threat intelligence at the same time that they are developing patching strategies,” he said. “That means knowing how the exploit is being utilized, which industries are being targeted, whether attackers are scanning for vulnerable APIs in large numbers, and what signs or actions may be watched throughout the patching time.”
While in-the-wild exploitation has not yet been acknowledged outside of the CISA KEV update, the likelihood has been strong as technical details and a Metasploit module were made public shortly after >HPE disclosed the flaw on December 18, 2025.
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Prometheus with Grafana Step-by-Step Guide for Observability

Introduction: Problem, Context & Outcome
Modern engineering teams manage complex systems where failures often appear without warning. Metrics exist, logs accumulate, and alerts fire constantly, yet teams still struggle to identify root causes quickly. As organizations adopt microservices, Kubernetes, and cloud platforms, system behavior becomes harder to predict. Legacy monitoring tools fail to adapt to dynamic infrastructure and rapid deployment cycles. Therefore, teams now require a metrics-driven observability approach designed for modern environments. Prometheus with Grafana delivers this capability by pairing robust metric collection with powerful visualization. This guide explains how the stack works, why it fits today’s DevOps workflows, and how teams use it effectively in production. Why this matters: Proactive observability prevents outages before they impact users.
What Is Prometheus with Grafana?
Prometheus with Grafana represents a popular open-source observability stack built for distributed and cloud-native systems. Prometheus collects time-series metrics from applications and infrastructure by scraping exposed endpoints. Grafana consumes those metrics and converts them into dashboards, charts, and alerts that teams understand easily. DevOps and SRE teams rely on this combination to monitor services, containers, Kubernetes clusters, and cloud resources. Prometheus focuses on reliable data collection and querying, while Grafana focuses on analysis, visualization, and collaboration. Organizations adopt this stack because it supports automation, scalability, and modern DevOps practices without vendor lock-in. Why this matters: Clear insight transforms raw metrics into operational awareness.
Why Prometheus with Grafana Is Important in Modern DevOps & Software Delivery
Modern DevOps relies on continuous delivery, fast feedback, and stable systems. CI/CD pipelines push changes frequently, and infrastructure changes dynamically. Traditional monitoring tools struggle to track short-lived workloads and containerized services. Prometheus with Grafana addresses these gaps through metrics-first observability built for dynamic environments. Teams validate deployments, monitor application health, and detect anomalies early. Prometheus integrates seamlessly with Kubernetes and cloud services. Grafana enables shared dashboards that align developers, DevOps engineers, and SREs. Enterprises adopt this stack to reduce downtime and improve release confidence. Why this matters: Observability directly influences delivery speed and system reliability.
Core Concepts & Key Components
Prometheus Metrics Scraping
Purpose: Collect consistent performance data continuously.
How it works: Prometheus scrapes metrics from HTTP endpoints that expose standardized metric formats.
Where it is used: Microservices, servers, containers, and Kubernetes clusters.
Why this matters: Metrics provide objective visibility into system behavior.
PromQL Query Engine
Purpose: Query and analyze metrics efficiently.
How it works: PromQL supports filtering, aggregation, and mathematical operations on time-series data.
Where it is used: Dashboards, alerts, and root-cause analysis.
Why this matters: Strong queries reveal trends and anomalies quickly.
Alertmanager
Purpose: Control how alerts reach teams.
How it works: Alertmanager groups, routes, and suppresses alerts based on rules.
Where it is used: Incident management and on-call rotations.
Why this matters: Organized alerts reduce noise and fatigue.
Grafana Dashboards
Purpose: Visualize metrics clearly for different audiences.
How it works: Grafana connects to Prometheus and renders interactive dashboards and charts.
Where it is used: Operations monitoring and executive reporting.
Why this matters: Visualization improves shared understanding.
Exporters and Integrations
Purpose: Extend metric coverage beyond applications.
How it works: Exporters expose metrics from databases, operating systems, and third-party services.
Where it is used: Infrastructure, cloud services, and platforms.
Why this matters: End-to-end coverage ensures complete observability.
Why this matters: These components together create a production-ready observability stack.
How Prometheus with Grafana Works (Step-by-Step Workflow)
The workflow begins when systems expose metrics through endpoints. Prometheus discovers these targets and scrapes metrics at defined intervals. The collected metrics store as time-series data. Engineers query the data using PromQL to examine trends and detect abnormalities. Grafana connects to Prometheus as a data source. Dashboards display real-time and historical metrics. Alert rules evaluate thresholds continuously. Alertmanager sends notifications when conditions trigger. Teams consult dashboards during releases and incidents. This workflow mirrors real DevOps lifecycles and CI/CD pipelines. Why this matters: Predictable workflows enable reliable monitoring at scale.
Real-World Use Cases & Scenarios
Organizations use Prometheus with Grafana to monitor Kubernetes clusters and cloud-native workloads. DevOps engineers track resource utilization and deployment stability. Developers observe latency and error rates after feature releases. QA teams validate performance during stress testing. SRE teams investigate incidents using historical metrics. Cloud teams monitor capacity trends and usage patterns. This shared observability improves collaboration and delivery outcomes. Why this matters: Unified visibility strengthens cross-team decision-making.
Benefits of Using Prometheus with Grafana
Teams gain deep insight into application and infrastructure health. Organizations detect issues before users experience failures. Automation improves alert precision. Collaboration improves through shared dashboards.
Productivity: Faster troubleshooting and analysis Reliability: Early detection of failures Scalability: Designed for dynamic systems Collaboration: Shared visibility across roles Why this matters: These benefits justify enterprise-wide adoption.
Challenges, Risks & Common Mistakes
Teams sometimes collect too many metrics without clear objectives. Beginners create excessive alerts that cause alert fatigue. Poor dashboard design hides important signals. Insufficient storage planning leads to data loss. Teams mitigate these risks through metric discipline and governance. Why this matters: Awareness prevents observability becoming operational debt.
Comparison Table
Traditional MonitoringPrometheus with GrafanaStatic checksDynamic metricsManual configurationService discoveryLimited scalabilityCloud-native scaleProprietary toolingOpen-source ecosystemReactive alertingProactive alertingWeak Kubernetes supportNative Kubernetes integrationData silosUnified dashboardsRigid queriesPromQL flexibilityHigh licensing costsCost-efficientSlow diagnosticsFaster root-cause analysis Why this matters: Comparison highlights modernization value clearly.
Best Practices & Expert Recommendations
Teams should define metric naming standards early. Alerts should focus on user-impacting symptoms. Dashboards should represent service health clearly. Retention policies should match compliance needs. Security controls should protect metric endpoints. Why this matters: Best practices ensure long-term success.
Who Should Learn or Use Prometheus with Grafana?
Developers benefit from insight into application behavior. DevOps engineers manage infrastructure monitoring effectively. Cloud, SRE, and QA professionals gain operational confidence. Beginners learn observability fundamentals, while experienced teams optimize complex platforms. Why this matters: Correct audience alignment maximizes learning outcomes.
FAQs – People Also Ask
What is Prometheus with Grafana?
It combines metrics collection and visualization. It supports modern observability. Why this matters: Clear understanding avoids confusion.
Why do DevOps teams use it?
It scales with cloud-native systems. It integrates with automation. Why this matters: Relevance drives adoption.
Is it suitable for beginners?
Yes, with proper guidance. Concepts remain accessible. Why this matters: Accessibility increases adoption.
Does it integrate with Kubernetes?
Yes, natively. Kubernetes ecosystems rely on it. Why this matters: Kubernetes requires metrics visibility.
How does it compare with legacy tools?
It scales better and adapts faster. Legacy tools remain static. Why this matters: Modern systems need modern monitoring.
Can it replace paid monitoring tools?
Often yes, with proper setup. Many enterprises rely on it. Why this matters: Cost efficiency matters.
Is Grafana mandatory with Prometheus?
No, but it improves clarity. Visualization adds value. Why this matters: Clear visuals improve decisions.
Does it support alerting?
Yes, through Alertmanager. Alerts become actionable. Why this matters: Fast response reduces downtime.
Is it production-ready?
Yes, widely used at scale. Stability remains proven. Why this matters: Production trust matters.
Is it valuable for DevOps careers?
Yes, demand continues growing. Skills stay relevant. Why this matters: Career growth depends on relevance.
Branding & Authority
DevOpsSchool operates as a globally trusted platform delivering enterprise-grade education in DevOps, cloud technologies, and observability. The platform provides structured programs, hands-on labs, and production-focused learning paths.
Rajesh Kumar offers mentorship backed by more than 20 years of hands-on experience across DevOps, DevSecOps, Site Reliability Engineering, DataOps, AIOps, MLOps, Kubernetes, cloud platforms, CI/CD, and automation.
The structured learning path for Prometheus with Grafana bridges observability theory with enterprise operations and modern DevOps workflows. Why this matters: Trusted expertise leads to job-ready skills.
Call to Action & Contact Information
Email: [email protected]
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iPhone Fold to Pave Way for Thinner, Brighter Display on iPhone Air 2

The iPhone Fold will be the first Apple device to adopt a Samsung-made OLED technology called CoE (Color Filter on Encapsulation), which could make the display brighter and thinner than previous panels, reports The Elec.


In a traditional OLED panel, a polarizing film sits above the display to cut reflections and improve contrast. The drawback is that this film also absorbs some of the OLED's own light, reducing brightness and efficiency. With CoE, Apple would remove the polarizer entirely and instead apply the color filter directly onto the OLED's protective encapsulation layer.

The result would be a thinner display stack that lets more light through, delivering higher brightness without requiring more power. Removing layers would also mean less thickness overall, potentially contributing to a slimmer iPhone design.

According to The Elec, Apple plans to debut CoE with its foldable iPhone, which could launch as soon as late 2026, before expanding the technology to the iPhone Air 2 in 2027. The latter's release has reportedly been pushed back following weaker-than-expected sales of the original iPhone Air.

Whether CoE will be applied and whether the iPhone Air 2 will be released will be decided by the third quarter of this year, according to industry sources cited by the Korean-language report.
iPhone Fold: Launch, Pricing, and What to Expect From Apple's Foldable
Samsung, meanwhile, plans to apply CoE not only to its foldable Galaxy Z Fold and Z Flip models, but also to the Galaxy S26 Ultra, expected in the first quarter of this year. The S26 Ultra will be Samsung's first non-foldable smartphone to use the technology, which the company refers to internally as OCF (On-Cell Film).Related Roundup: iPhone AirTag: Foldable iPhoneBuyer's Guide: iPhone Air (Buy Now)
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Cybersecurity Predictions 2026: The Hype We Can Ignore (And the Risks We Can't)

As organizations plan for 2026, cybersecurity predictions are everywhere. Yet many strategies are still shaped by headlines and speculation rather than evidence. The real challenge isn’t a lack of forecasts—it’s identifying which predictions reflect real, emerging risks and which can safely be ignored. An upcoming webinar hosted by Bitdefender aims to cut through the noise with a data-drivenView the full article
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NoOps Foundation Step-by-Step Guide for Cloud-Native Platforms

Introduction: Problem, Context & Outcome
Engineering teams repeatedly struggle because operational overhead consumes time meant for innovation. Many organizations still handle infrastructure through manual provisioning, ticket queues, and reactive firefighting. These patterns reduce release velocity and increase reliability risks. As cloud ecosystems mature, enterprises expect faster delivery without growing operational complexity. Therefore, NoOps has emerged as a model that minimizes human intervention through automation and managed platforms. The NoOps Foundation Certification helps professionals understand how this shift works in real production environments. This guide explains why NoOps matters, how it complements DevOps, and how the certification prepares teams for modern cloud-native delivery. Readers gain clarity on concepts, workflows, benefits, and real-world adoption. Why this matters: Lower operational friction directly improves engineering productivity.
What Is NoOps Foundation Certification?
The NoOps Foundation Certification provides foundational knowledge for operating systems with near-zero manual operational effort. Rather than replacing DevOps, NoOps extends DevOps practices by transferring repeatable operational tasks to automation, cloud services, and self-healing mechanisms. This certification explains how infrastructure provisioning, scaling, monitoring, and failure recovery occur automatically through predefined rules. Developers and DevOps engineers use these principles to eliminate routine operational work while maintaining reliability. Additionally, NoOps aligns closely with serverless computing, managed services, and platform engineering initiatives. Organizations use this certification to build a shared understanding of what NoOps truly means. Why this matters: Clear foundations prevent unrealistic expectations and misuse of NoOps.
Why NoOps Foundation Certification Is Important in Modern DevOps & Software Delivery
Modern software delivery depends on automation, consistency, and speed. CI/CD pipelines, Agile practices, and cloud-native architectures all demand minimal manual intervention. Operational bottlenecks slow deployments and increase error rates. NoOps addresses these challenges by reducing or eliminating repetitive operational tasks. Therefore, the NoOps Foundation Certification equips teams to design systems that align with DevOps goals while reducing operational complexity. Enterprises increasingly adopt NoOps models to lower infrastructure costs, simplify management, and improve recovery times. Why this matters: Automation now defines competitive software delivery.
Core Concepts & Key Components
Automation-First Operations
Purpose: Remove repetitive operational activities.
How it works: Automation provisions infrastructure, manages scaling, and handles recovery using rules.
Where it is used: CI/CD pipelines and cloud platforms.
Why this matters: Automation reduces errors and accelerates releases.
Managed Cloud Services
Purpose: Shift maintenance responsibility away from teams.
How it works: Teams rely on managed databases, queues, and compute services.
Where it is used: Public and hybrid cloud environments.
Why this matters: Managed services reduce operational workload.
Serverless Computing
Purpose: Eliminate server administration.
How it works: Cloud platforms execute code on demand with automatic scaling.
Where it is used: Event-driven systems and APIs.
Why this matters: Serverless shortens development cycles.
Platform Engineering
Purpose: Abstract infrastructure complexity.
How it works: Internal platforms provide standardized self-service workflows.
Where it is used: Enterprises with multiple engineering teams.
Why this matters: Platforms enforce consistency and safety.
Observability and Self-Healing
Purpose: Detect and resolve issues automatically.
How it works: Monitoring signals trigger remediation workflows.
Where it is used: Cloud-native production systems.
Why this matters: Self-healing improves availability.
Why this matters: These elements turn NoOps into a practical operating model.
How NoOps Foundation Certification Works (Step-by-Step Workflow)
The workflow starts with designing applications for automation and managed platforms. Teams select cloud-native services that minimize operational responsibility. Infrastructure provisioning occurs automatically using pipelines and templates. CI/CD systems deploy applications continuously without manual approvals. Observability tools collect metrics, logs, and traces in real time. Alerting systems initiate automated recovery actions when anomalies appear. Engineers focus on improving applications instead of managing servers. Why this matters: Defined workflows make NoOps sustainable at scale.
Real-World Use Cases & Scenarios
Startups adopt NoOps to ship products rapidly without dedicated operations teams. Enterprises apply NoOps to modernize legacy systems using managed cloud platforms. DevOps engineers build automation pipelines and guardrails. Developers deploy applications independently through self-service portals. QA teams validate behavior without provisioning infrastructure. SRE teams oversee reliability through observability systems. These scenarios reduce costs and accelerate delivery. Why this matters: Real-world adoption proves NoOps works.
Benefits of Using NoOps Foundation Certification
Organizations gain a clear understanding of automation-driven operations. Teams reduce time spent on infrastructure tasks. Automation improves consistency across environments. Collaboration improves due to simplified responsibilities.
Productivity: Engineers focus on features Reliability: Automation reduces incidents Scalability: Platforms scale automatically Collaboration: Fewer operational handoffs Why this matters: Benefits directly support business outcomes.
Challenges, Risks & Common Mistakes
Teams sometimes believe NoOps eliminates responsibility entirely. Poor automation design introduces hidden risks. Excessive vendor dependency reduces flexibility. Weak observability creates blind spots. Successful NoOps adoption requires governance, planning, and operational awareness. Why this matters: Understanding risks prevents costly failures.
Comparison Table
Traditional OperationsDevOpsNoOpsManual provisioningAutomated pipelinesManaged platformsTicket-based workflowsCI/CD workflowsSelf-service deliveryServer maintenanceInfrastructure as CodeServerless executionReactive recoveryAutomated recoverySelf-healing systemsHigh overheadReduced overheadMinimal overheadSlow scalingOn-demand scalingAutomatic scalingOperations silosDev-Ops alignmentPlatform-led deliveryManual monitoringCentral monitoringAutonomous observabilityHeavy maintenanceModerate maintenanceLow maintenanceSlow innovationFaster deliveryFeature-focused teams Why this matters: Comparison clarifies operational evolution.
Best Practices & Expert Recommendations
Teams should adopt NoOps incrementally. Automation choices must align with business goals. Observability should remain mandatory. Governance should control automated decisions. Documentation must stay current and accessible. Why this matters: Best practices ensure safe, scalable adoption.
Who Should Learn or Use NoOps Foundation Certification?
Developers building cloud-native applications gain immediate value. DevOps engineers transitioning into platform roles benefit greatly. Cloud, SRE, and QA professionals improve operational clarity. Beginners learn modern models, while experienced teams refine strategy. Why this matters: Correct audience targeting maximizes return on learning.
FAQs – People Also Ask
What is NoOps Foundation Certification?
It explains NoOps fundamentals. It focuses on automation. Why this matters: Foundations guide adoption.
Does NoOps eliminate DevOps roles?
No, it evolves responsibilities. Automation handles routine tasks. Why this matters: Roles adapt over time.
Is NoOps suitable for enterprises?
Yes, with proper governance. Many enterprises adopt it. Why this matters: Scale requires structure.
Is it beginner-friendly?
Yes, it emphasizes concepts. It avoids deep tooling. Why this matters: Accessibility supports learning.
How does NoOps relate to serverless?
Serverless enables NoOps models. Both reduce operations. Why this matters: Concepts align closely.
Does NoOps support CI/CD?
Yes, automation strengthens pipelines. Delivery speeds increase. Why this matters: Speed improves competitiveness.
Is monitoring still required?
Yes, observability remains essential. Automation depends on signals. Why this matters: Visibility ensures reliability.
Does NoOps increase vendor lock-in?
It can without planning. Strategy mitigates risk. Why this matters: Balance preserves flexibility.
Can SRE teams work with NoOps?
Yes, SRE complements NoOps. Reliability remains central. Why this matters: Roles align naturally.
Is NoOps future-proof?
Yes, automation demand continues growing. Cloud platforms evolve rapidly. Why this matters: Skills remain relevant.
Branding & Authority
DevOpsSchool operates as a globally trusted learning platform delivering enterprise-grade education in DevOps, cloud computing, automation, and modern operational models. Professionals worldwide rely on its structured programs, hands-on labs, and real-world training aligned with production environments. Why this matters: Trusted platforms ensure enterprise-ready learning.
Rajesh Kumar brings more than 20 years of hands-on industry experience across DevOps, DevSecOps, Site Reliability Engineering, DataOps, AIOps, MLOps, Kubernetes, cloud platforms, CI/CD, and large-scale automation. His mentorship emphasizes real operational execution. Why this matters: Experience bridges learning and production.
The structured learning path for the NoOps Foundation Certification connects automation-first principles with cloud-native platforms and enterprise delivery models. Why this matters: Industry-aligned certification builds job-ready expertise.
Call to Action & Contact Information
To explore structured learning for the NoOps Foundation Certification, connect with the team below.
Email: [email protected]
Phone & WhatsApp (India): +91 7004215841
Phone & WhatsApp (USA): +1 (469) 756-6329




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MLOps Foundation Hands-On Tutorial for Modern DevOps

Introduction: Problem, Context & Outcome
Many organizations succeed at building machine learning models but fail when deploying them into real production environments. Teams often rely on manual processes, untracked data changes, and disconnected workflows between data scientists and DevOps engineers. These gaps lead to unreliable releases, model failures, and lost business value. As AI adoption accelerates across industries, companies can no longer afford experimental ML practices in production systems. Therefore, teams must adopt structured operational approaches that align ML with DevOps principles. The MLOps Foundation Certification provides this foundational understanding by introducing standardized workflows for building, deploying, monitoring, and governing machine learning systems. This guide explains what the certification covers, why enterprises require it, and how professionals apply it in real-world environments. Why this matters: Operational discipline determines whether AI succeeds or fails.
What Is MLOps Foundation Certification?
The MLOps Foundation Certification defines the essential knowledge required to operate machine learning systems reliably at scale. Instead of concentrating only on model development, this certification focuses on operational stability, collaboration, automation, and governance. It explains how teams manage datasets, experiments, models, pipelines, and monitoring across development and production stages. Developers, DevOps engineers, ML engineers, and platform teams use these principles to support enterprise-grade AI platforms. Moreover, the certification bridges the gap between experimentation and software delivery. Organizations adopt it to create a shared operational foundation across technical roles. Why this matters: Common foundations eliminate friction between ML and DevOps teams.
Why MLOps Foundation Certification Is Important in Modern DevOps & Software Delivery
Modern software delivery pipelines increasingly include machine learning components alongside traditional applications. CI/CD pipelines, cloud-native platforms, and Agile practices demand repeatability and control. Machine learning introduces challenges such as model drift, reproducibility issues, and environment inconsistency. Therefore, the MLOps Foundation Certification teaches teams how to extend DevOps practices to ML workflows. It supports automated testing, continuous delivery, monitoring, and governance for ML systems. Enterprises rely on these practices to meet compliance requirements and maintain system reliability. Why this matters: DevOps without MLOps cannot support AI-driven products.
Core Concepts & Key Components
ML Lifecycle Management
ML lifecycle management defines how teams control models from data ingestion through retirement. Engineers track datasets, experiments, versions, approvals, and deployments across environments. Enterprises apply this practice to maintain transparency and accountability. Why this matters: Lifecycle visibility prevents uncontrolled changes.
Data and Feature Versioning
Production data evolves continuously. MLOps enforces strict version control for datasets and features. Teams rely on this approach in regulated industries and high-impact systems. Why this matters: Versioned data ensures reproducibility.
Automated Training and Validation
This component introduces repeatable training pipelines with automated validation steps. Teams verify accuracy, bias, and performance before deployment. Production ML systems depend heavily on these controls. Why this matters: Automation reduces human error.
CI/CD for Machine Learning
MLOps extends CI/CD pipelines to ML artifacts. Teams build, test, and deploy models using standardized pipelines. Organizations use this method to scale AI delivery safely. Why this matters: Consistent delivery improves reliability.
Monitoring and Model Drift Detection
Models degrade as real-world data patterns change. MLOps introduces monitoring for accuracy, latency, and drift. SRE and DevOps teams depend on these signals daily. Why this matters: Monitoring protects business outcomes.
Governance, Security, and Compliance
This component ensures audit trails, access control, and policy enforcement. Enterprises adopt governance frameworks to meet legal, ethical, and security requirements. Why this matters: Responsible AI requires accountability.
Why this matters: Together, these components transform experiments into production systems.
How MLOps Foundation Certification Works (Step-by-Step Workflow)
The workflow begins with standardized data ingestion and preparation. Teams document assumptions and version datasets from the start. Automated pipelines then train models and record experiments. Validation steps confirm quality and fairness before approval. Deployment pipelines release models into controlled environments. Monitoring systems track performance and drift continuously. Feedback loops trigger retraining or rollback when metrics decline. This workflow mirrors real DevOps lifecycles while addressing ML-specific challenges. Why this matters: Structured workflows remove uncertainty.
Real-World Use Cases & Scenarios
Organizations use MLOps to deliver fraud detection systems, recommendation engines, demand forecasting platforms, and predictive maintenance solutions. DevOps engineers manage infrastructure and CI/CD pipelines. Developers integrate models into applications. QA teams validate outputs and edge cases. SRE teams monitor performance and reliability. These coordinated roles improve system stability and delivery speed. Why this matters: Cross-team collaboration drives success.
Benefits of Using MLOps Foundation Certification
Teams gain a shared understanding of ML operations. Organizations improve release reliability and visibility. Automation lowers operational risk. Standardization supports scaling across teams and platforms.
Improved productivity Higher reliability Scalable ML delivery Strong collaboration Why this matters: Benefits increase as AI usage grows.
Challenges, Risks & Common Mistakes
Teams often underestimate the operational complexity of ML systems. Beginners may skip monitoring or governance steps. Environment inconsistencies cause deployment failures. Poor communication delays delivery. MLOps addresses these risks through structured processes. Why this matters: Awareness prevents expensive incidents.
Comparison Table
Traditional MLMLOps-Driven MLManual processesAutomated pipelinesNo data versioningFull traceabilityAd-hoc deploymentsCI/CD integrationLimited monitoringContinuous monitoringData silosGoverned datasetsOne-off modelsReusable systemsHigh failure riskPredictable deliveryWeak collaborationCross-team alignmentNo audit trailsCompliance readyLimited scalabilityCloud-native scalability Why this matters: Comparison shows the operational advantage clearly.
Best Practices & Expert Recommendations
Teams should define ownership across ML and DevOps roles. Automation must cover training, testing, and deployment. Monitoring should track both technical and business metrics. Documentation should remain accurate. Governance policies should align with enterprise standards. Why this matters: Best practices prevent long-term technical debt.
Who Should Learn or Use MLOps Foundation Certification?
Developers building ML-enabled applications gain operational clarity. DevOps engineers learn how to manage ML pipelines effectively. Cloud, SRE, and QA professionals strengthen delivery alignment. Beginners build strong foundations, while experienced teams refine workflows. Why this matters: The right skills improve outcomes.
FAQs – People Also Ask
What is MLOps Foundation Certification?
It validates foundational MLOps knowledge. It focuses on production readiness. Why this matters: Foundations enable scale.
Why is MLOps important?
It ensures reliable ML delivery. It prevents failures. Why this matters: Reliability builds trust.
Is this certification beginner-friendly?
Yes, it emphasizes concepts. It avoids heavy mathematics. Why this matters: Accessibility increases adoption.
Does it help DevOps engineers?
Yes, it aligns ML with CI/CD pipelines. It improves workflows. Why this matters: DevOps teams support AI.
Does it include monitoring?
Yes, it covers drift detection and metrics. It supports accuracy. Why this matters: Monitoring sustains value.
Is it relevant for cloud environments?
Yes, it supports scalable cloud platforms. It aligns with cloud-native practices. Why this matters: Cloud hosts modern AI.
Can enterprises standardize on it?
Yes, many organizations adopt it. It creates consistency. Why this matters: Standards reduce risk.
How does it differ from ML courses?
It focuses on operations. It prepares teams for production. Why this matters: Production skills matter most.
Does it address governance?
Yes, it supports audits and compliance. It enforces accountability. Why this matters: Governance protects businesses.
Is it future-proof?
Yes, AI adoption continues to expand. Demand for MLOps skills grows. Why this matters: Skills remain valuable.
Branding & Authority
DevOpsSchool serves as a trusted global platform for DevOps, cloud computing, and AI operations training. Professionals worldwide access structured programs, hands-on labs, and real-world scenarios through DevOpsSchool .
Rajesh Kumar brings over 20 years of hands-on experience across DevOps, DevSecOps, SRE, DataOps, AIOps, MLOps, Kubernetes, cloud platforms, CI/CD, and automation, supported by Rajesh Kumar.
The learning path for the MLOps Foundation Certification remains available at MLOps Foundation Certification and closely aligns with enterprise operational needs. Why this matters: Proven expertise ensures production-ready learning.
Call to Action & Contact Information
Email: [email protected]
Phone & WhatsApp (India): +91 7004215841
Phone & WhatsApp (USA): +1 (469) 756-6329




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Complete MLOps Tutorial for AI-Driven IT Operations

Introduction: Problem, Context & Outcome
Many organizations invest in machine learning to automate decisions and improve products. However, serious gaps appear when models move from experiments to live systems. Models that perform well during testing often fail in production because updates happen manually, monitoring is ignored, and teams lack clear ownership. As a result, performance drops, errors remain hidden, and business trust declines. In addition, data scientists, developers, and DevOps teams frequently work in isolation, which slows delivery and increases risk.
MLOps Certified Professional exists to close this gap. It brings structure to how machine learning systems are built, deployed, and maintained. By combining DevOps practices with machine learning workflows, teams gain control, visibility, and repeatability.
This blog explains what MLOps Certified Professional is, why it matters today, and how it helps teams deliver reliable machine learning systems in real-world environments.
Why this matters: Without proper MLOps practices, most machine learning projects fail after deployment and lose business value.
What Is MLOps Certified Professional?
MLOps Certified Professional is a structured learning path focused on operating machine learning systems in production. Instead of stopping at model training, it covers the complete lifecycle of a model, including data preparation, training, testing, deployment, monitoring, and ongoing improvement.
Machine learning systems depend on multiple components such as data pipelines, infrastructure, applications, and monitoring tools. MLOps Certified Professional teaches how to manage all these components together in a practical and controlled way. It helps teams move from experimental notebooks to production-ready systems.
The program focuses on real enterprise challenges rather than theory. Common production issues such as failed deployments, data changes, and performance loss are explained clearly with practical solutions. You can explore the full curriculum in the MLOps Certified Professional program.
Why this matters: Machine learning only delivers results when models run reliably in production environments.
Why MLOps Certified Professional Is Important in Modern DevOps & Software Delivery
Modern software delivery relies on automation, CI/CD pipelines, and cloud platforms to release changes quickly and safely. However, many teams keep machine learning outside these workflows, which creates manual steps and repeated failures.
MLOps Certified Professional brings machine learning into the DevOps lifecycle. Teams treat models like software artifacts, which means they version, test, deploy, and monitor them using the same pipelines as application code. As a result, releases become predictable and easier to manage.
In CI/CD pipelines, models are validated before deployment. In cloud environments, infrastructure scales efficiently while costs stay under control. In Agile teams, experimentation continues without risking production stability.
MLOps Certified Professional ensures machine learning fits naturally into modern software delivery.
Why this matters: Machine learning cannot scale or remain stable without DevOps discipline.
Core Concepts & Key Components
Model Lifecycle Management
Purpose: Manage models from creation to retirement.
How it works: Teams version models, deploy them, monitor their performance, and replace them when needed.
Where it is used: Production machine learning systems.
Data Management and Versioning
Purpose: Maintain data consistency and traceability.
How it works: Teams track data versions and automate data pipelines.
Where it is used: Training workflows and feature engineering systems.
CI/CD for Machine Learning
Purpose: Automate testing and deployment of models.
How it works: Pipelines validate models before production release.
Where it is used: Cloud-based and enterprise ML platforms.
Model Monitoring and Drift Detection
Purpose: Identify performance drops early.
How it works: Teams monitor predictions and data changes over time.
Where it is used: Live prediction services and APIs.
Infrastructure and Environment Management
Purpose: Keep environments stable and repeatable.
How it works: Teams provision and manage infrastructure using automation tools.
Where it is used: Training and deployment environments.
Why this matters: When all components work together, machine learning systems remain reliable and trustworthy.
How MLOps Certified Professional Works (Step-by-Step Workflow)
Teams begin by preparing data and storing clear versions to ensure consistent training across environments. Next, they train and test models in controlled systems and approve only those that meet quality standards.
After approval, CI/CD pipelines deploy models automatically to staging and production environments. At the same time, infrastructure automation keeps environments consistent and predictable.
Once models go live, teams monitor performance and data quality continuously. When accuracy drops or data patterns change, retraining pipelines update models safely without service disruption.
This workflow follows the same principles used in modern DevOps delivery.
Why this matters: A repeatable workflow reduces errors and protects production systems.
Real-World Use Cases & Scenarios
Financial organizations use MLOps to update fraud detection models without downtime. DevOps and SRE teams maintain stability while data teams improve accuracy.
Retail companies use MLOps pipelines to refresh recommendation systems as customer behavior evolves. Developers integrate models into applications and track business outcomes.
Healthcare organizations apply MLOps to validate models carefully before deployment. QA teams test outputs, while cloud teams manage secure and compliant releases.
Across industries, MLOps improves delivery speed and operational confidence.
Why this matters: Businesses rely on consistent machine learning results for critical decisions.
Benefits of Using MLOps Certified Professional
Productivity: Automation reduces manual effort Reliability: Early detection prevents silent failures Scalability: Systems grow smoothly with data and demand Collaboration: Teams align across data, DevOps, and engineering Why this matters: These benefits help organizations succeed with machine learning over the long term.
Challenges, Risks & Common Mistakes
Teams often deploy models manually and delay monitoring, which leads to late discovery of failures. Problems also arise when machine learning workflows remain separate from DevOps pipelines.
MLOps Certified Professional reduces these risks by promoting automation, testing, and shared responsibility across teams.
Why this matters: Most machine learning failures come from weak processes, not model quality.
Comparison Table
Traditional ML ApproachMLOps ApproachManual deploymentAutomated pipelinesNo version controlClear version trackingNo monitoringContinuous monitoringStatic modelsRegular updatesSiloed teamsCross-team collaborationLocal environmentsCloud environmentsRisky releasesSafe releasesSlow recoveryFaster recoveryLow trustHigh trustUnstable systemsStable systems Why this matters: Modern machine learning requires modern delivery and operations practices.
Best Practices & Expert Recommendations
Teams should automate early and treat models like software. Monitoring should run on every production model, and results should be reviewed regularly. Cloud resources should be used carefully to balance scale and cost.
Strong collaboration between data teams, DevOps engineers, QA teams, and SREs leads to better outcomes and fewer risks.
Why this matters: Consistent best practices prevent repeated failures and support steady growth.
Who Should Learn or Use MLOps Certified Professional?
Developers, DevOps engineers, cloud engineers, QA professionals, SREs, and data engineers benefit from this program. It suits professionals with basic experience who want to manage machine learning systems in production.
Organizations adopting machine learning at scale gain the most value.
Why this matters: The right audience ensures long-term MLOps success.
FAQs – People Also Ask
What is MLOps Certified Professional?
It focuses on managing machine learning in production systems.
Why this matters:
Why do teams need MLOps?
Teams need it to keep systems reliable and stable.
Why this matters:
Is the program beginner friendly?
Yes, basic knowledge is enough to begin.
Why this matters:
Does it include CI/CD practices?
Yes, CI/CD is a core part of the program.
Why this matters:
Does it support cloud platforms?
Yes, cloud usage is essential.
Why this matters:
Does it include monitoring?
Yes, teams track model results and data changes.
Why this matters:
Is it vendor specific?
No, the principles apply across platforms.
Why this matters:
Can QA teams use MLOps?
Yes, QA teams validate model outputs.
Why this matters:
Do enterprises use MLOps today?
Yes, it is widely adopted.
Why this matters:
Does it help DevOps teams?
Yes, it aligns ML with DevOps workflows.
Why this matters:
Branding & Authority
DevOpsSchool is a globally trusted learning platform delivering hands-on training in DevOps, cloud, and automation. Its programs focus on real enterprise systems and real production challenges to help learners build job-ready skills.
Rajesh Kumar leads the training with more than 20 years of hands-on experience across DevOps, DevSecOps, Site Reliability Engineering (SRE), DataOps, AIOps, MLOps, Kubernetes, cloud platforms, and CI/CD systems. His guidance connects learning directly to real-world delivery.
Why this matters: Real industry experience ensures learning turns into practical, usable skills.
Call to Action & Contact Information
Explore the MLOps Certified Professional program to build reliable and scalable machine learning systems.
Email: [email protected]
Phone & WhatsApp (India): +91 7004215841
Phone & WhatsApp (USA): +1 (469) 756-6329

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Trend Micro Apex Central RCE Flaw Scores 9.8 CVSS in On-Prem Windows Versions

Trend Micro has released security updates to address multiple security vulnerabilities impacting on-premise versions of Apex Central for Windows, including a critical bug that could result in arbitrary code execution. The vulnerability, tracked as CVE-2025-69258, carries a CVSS score of 9.8 out of a maximum of 10.0. The vulnerability has been described as a case of remote code executionView the full article
Hacker News

A Comprehensive Guide to AZ-500 for Cloud Security Engineers

Introduction: Problem, Context & Outcome
Many organizations rely on Microsoft Azure to run applications, manage data, and release software faster. While the cloud makes work easier, it also brings new security risks. Simple mistakes like giving too much access, weak login rules, or missing alerts can lead to data leaks or system downtime. DevOps teams often focus on speed, and security is sometimes handled after systems are already live.
Microsoft Azure Security Technologies (AZ-500) helps teams avoid these problems. It teaches how to include security at every stage of cloud work. Security becomes part of daily operations instead of a late fix. Teams can move fast while still protecting systems and data.
In this blog, you will learn what AZ-500 is, how it works, and how it supports real teams in real environments.
Why this matters: Cloud security issues can interrupt services, damage trust, and cause serious business impact.
What Is Microsoft Azure Security Technologies (AZ-500)?
Microsoft Azure Security Technologies (AZ-500) is a cloud security learning path that focuses on protecting systems built on Microsoft Azure. It explains how to secure users, networks, servers, applications, and data using Azure’s native security features.
This topic is practical and focused on real work. It helps developers, DevOps engineers, and cloud professionals understand how to manage access, protect sensitive data, and detect security problems early. Instead of focusing only on theory, AZ-500 shows how security tools are used in daily cloud operations.
AZ-500 also helps connect development, operations, and security teams by giving them a shared approach and common tools. This reduces confusion and improves teamwork.
Details about the training structure are available through the Microsoft Azure Security Technologies (AZ-500) program.
Why this matters: Clear and practical security knowledge helps teams prevent common Azure risks before they grow.
Why Microsoft Azure Security Technologies (AZ-500) Is Important in Modern DevOps & Software Delivery
Modern DevOps teams aim to deliver changes quickly and often. Automation and rapid feedback are key goals. However, fast delivery without proper security can increase risk. AZ-500 helps teams apply security in a way that supports DevOps rather than slowing it down.
With AZ-500 practices, access control, network protection, and monitoring are set up using automation. Security rules are applied consistently across environments. This allows teams to release software frequently without exposing systems to unnecessary risk.
In CI/CD pipelines, AZ-500 concepts help protect credentials and limit access. In cloud environments, they help teams detect unusual activity early and respond quickly.
Security becomes part of the delivery flow, not a roadblock.
Why this matters: Speed in DevOps is only useful when systems remain secure and reliable.
Core Concepts & Key Components
Identity and Access Management
Purpose: Decide who can access Azure resources and what they can do.
How it works: Uses role-based access, clear login rules, and controlled permissions.
Where it is used: User accounts, services, automation scripts, and pipelines.
Network Security
Purpose: Protect traffic between Azure systems.
How it works: Uses firewalls, private networks, and access rules.
Where it is used: Virtual networks and application connections.
Platform Protection
Purpose: Secure servers, containers, and platforms.
How it works: Checks systems for unsafe settings and known risks.
Where it is used: Virtual machines, containers, and managed services.
Data and Storage Security
Purpose: Keep data safe from unauthorized access.
How it works: Uses encryption and secure key handling.
Where it is used: Databases, file storage, and backups.
Security Monitoring and Governance
Purpose: Watch systems and enforce security rules.
How it works: Uses logs, alerts, and policies.
Where it is used: Monitoring, audits, and compliance processes.
Why this matters: Multiple security layers reduce damage even if one control fails.
How Microsoft Azure Security Technologies (AZ-500) Works (Step-by-Step Workflow)
The process starts by setting access rules. Users and services receive only the permissions they need. This reduces mistakes and misuse.
Next, network controls are applied. Systems communicate only where required. Unused or risky paths are blocked.
Then, security tools scan systems regularly. Weak settings and risks are identified early and corrected.
After that, data is protected using encryption and secure storage methods.
Finally, monitoring tools track system activity. Alerts are raised when something unusual happens so teams can act quickly.
This workflow fits naturally into DevOps pipelines and cloud operations.
Why this matters: A repeatable process makes security easier to manage and scale.
Real-World Use Cases & Scenarios
Software companies use AZ-500 practices to secure their CI/CD pipelines and prevent secrets from being exposed.
Banks and healthcare organizations rely on these security controls to meet strict rules while still releasing updates on time.
SRE teams use monitoring and alerts to respond to security issues quickly and reduce downtime.
Developers benefit from safer platforms that reduce rework and unexpected issues.
Why this matters: Strong security improves delivery speed and system stability.
Benefits of Using Microsoft Azure Security Technologies (AZ-500)
Productivity: Less manual security work and fewer delays Reliability: Reduced outages caused by security issues Scalability: Security that grows with cloud systems Collaboration: Clear responsibilities across teams Why this matters: Simple and consistent security supports long-term growth.
Challenges, Risks & Common Mistakes
Common mistakes include giving too much access, relying only on default settings, and adding security after deployment.
These risks can be reduced by using clear roles, regular reviews, and automation.
Why this matters: Most Azure security incidents start with small and avoidable errors.
Comparison Table
Traditional ApproachAZ-500 ApproachManual access setupRole-based accessOpen network pathsProtected networksOne-time checksContinuous checksLate security setupBuilt-in securitySiloed teamsShared responsibilityStored secretsSecure identitiesManual auditsPolicy-driven controlSlow alertsFaster alertsLimited visibilityClear dashboardsHigher riskLower risk Why this matters: Cloud security must match the speed and scale of modern systems.
Best Practices & Expert Recommendations
Give only the access that is required. Review permissions regularly. Automate security rules wherever possible. Monitor systems every day.
Use Azure’s built-in security tools before adding extra tools to reduce complexity.
Why this matters: Good practices prevent most security problems before they occur.
Who Should Learn or Use Microsoft Azure Security Technologies (AZ-500)?
This topic is useful for developers, DevOps engineers, cloud engineers, SREs, and QA professionals working with Azure environments.
Basic Azure experience is helpful, but motivated learners can grow into the role over time.
Why this matters: Security knowledge improves confidence and performance across all roles.
FAQs – People Also Ask
What is Microsoft Azure Security Technologies (AZ-500)?
It teaches how to secure systems running on Azure.
Why this matters:
Is AZ-500 useful for DevOps engineers?
Yes, it aligns security with DevOps workflows.
Why this matters:
Is AZ-500 beginner friendly?
Yes, with basic Azure knowledge.
Why this matters:
Does AZ-500 cover access management?
Yes, it focuses strongly on access control.
Why this matters:
Does AZ-500 include monitoring?
Yes, for early detection of issues.
Why this matters:
Is AZ-500 helpful for compliance needs?
Yes, it supports audits and security rules.
Why this matters:
Is AZ-500 only for Azure platforms?
Yes, it is Azure specific.
Why this matters:
Does AZ-500 help application developers?
Yes, it supports safer application design.
Why this matters:
Is the learning practical?
Yes, it is based on real scenarios.
Why this matters:
Is AZ-500 suitable for large teams?
Yes, it scales well.
Why this matters:
Branding & Authority
DevOpsSchool is a globally trusted learning platform known for delivering hands-on, job-ready training in DevOps, cloud, and security. Its programs are built around real enterprise challenges and help learners move step by step from basic concepts to production-ready skills.
Training and guidance are led by Rajesh Kumar, a respected industry expert with over 20 years of hands-on experience. His background includes DevOps, DevSecOps, Site Reliability Engineering (SRE), DataOps, AIOps, MLOps, Kubernetes, cloud platforms, CI/CD automation, monitoring, and large enterprise systems. He is widely known for explaining complex topics in a clear and practical way.
The Microsoft Azure Security Technologies (AZ-500) program reflects this real-world approach and focuses on solving everyday Azure security challenges faced by DevOps and cloud teams.
Why this matters: Learning from trusted experts ensures skills are useful in real work environments, not just exams.
Call to Action & Contact Information
Email: [email protected]
Phone & WhatsApp (India): +91 7004215841
Phone & WhatsApp (USA): +1 (469) 756-6329

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CISA Retires 10 Emergency Cybersecurity Directives Issued Between 2019 and 2024

The U.S. Cybersecurity and Infrastructure Security Agency (CISA) on Thursday said it's retiring 10 emergency directives (Eds) that were issued between 2019 and 2024. The list of the directives now considered closed is as follows - ED 19-01: Mitigate DNS Infrastructure Tampering ED 20-02: Mitigate Windows Vulnerabilities from January 2020 Patch Tuesday ED 20-03: Mitigate Windows DNS ServerView the full article
Hacker News

AI CyberCon Summit 2026

Event Date: 10 January 2026
Venue: T-Hub, Hyderabad
AI CyberCon Summit 2026 is India’s leading summit on Artificial Intelligence, Cybersecurity, Fraud Prevention, Digital Trust & Compliance, bringing together:
CXOs, CISOs, CTOs
AI Innovators & Cybersecurity Leaders
Fintech & Enterprise Tech Professionals
Policymakers & Government Representatives
500+ Industry Decision Makers
The summit will feature:
-High-impact keynotes & panel discussions
-Live cyberattack simulations & hands-on workshops
-Sessions on AI governance, AML, Zero Trust & compliance
-Exhibition zone for technology showcases
-Strategic networking opportunities
A powerful platform designed to strengthen India’s secure AI transformation and digital resilience.
The post AI CyberCon Summit 2026 appeared first on CISO MAG | Cyber Security Magazine.
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CISOmag

Funk von kritischer Infrastruktur leicht abhörbar

Mangkorn Danggura – shutterstock.com
Etliche Einrichtungen der kritischen Infrastruktur in Deutschland kommunizieren mit ungeschützter Funktechnik. Der Digitalfunk zahlreicher Haftanstalten, Flughäfen und Energieversorger lässt sich mit geringem technischen Aufwand auch aus der Ferne abhören, weil die Betreiber auf die Verschlüsselung ihrer Netze verzichten, wie die “Wirtschaftswoche” berichtet.
Die AG Kritis, eine anerkannte unabhängige Arbeitsgruppe von Fachleuten für den Schutz kritischer Infrastrukturen, beklagte im Magazin: “Dass kritische Infrastruktur über ungesicherte Funknetze kommuniziert, ist ein sicherheitspolitisches Armutszeugnis.” Man öffne Angreifern Tür und Tor, gefährde die Versorgungssicherheit und letztlich Menschenleben, sagte der Sprecher der AG, Thomas Blinn. 
Dem Bericht nach reicht ein Laptop, eine frei verfügbare Software sowie etwas technisches Verständnis, um die Gespräche abzuhören. Dabei könnten auch vertrauliche oder sensible Informationen abgefangen werden. 
Auf Verschlüsselung verzichtet
In Deutschland sind mehr als 300 digitale Funknetze auf Basis des Tetra-Standards aktiv. Das ist eine Technik, auf der auch der Polizeifunk basiert. Dieser ist mehrfach verschlüsselt und gilt als abhörsicher. In mehreren Haftanstalten, Flughäfen sowie bei Energieversorgungseinrichtungen werde jedoch eine Version des Tetra-Netzes eingesetzt, die ohne Verschlüsselung auskomme, schrieb das Magazin und verwies auf Kostengründe. (dpa/jm)

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CSOonline

Funk von kritischer Infrastruktur leicht abhörbar

Mangkorn Danggura – shutterstock.com
Etliche Einrichtungen der kritischen Infrastruktur in Deutschland kommunizieren mit ungeschützter Funktechnik. Der Digitalfunk zahlreicher Haftanstalten, Flughäfen und Energieversorger lässt sich mit geringem technischen Aufwand auch aus der Ferne abhören, weil die Betreiber auf die Verschlüsselung ihrer Netze verzichten, wie die “Wirtschaftswoche” berichtet.
Die AG Kritis, eine anerkannte unabhängige Arbeitsgruppe von Fachleuten für den Schutz kritischer Infrastrukturen, beklagte im Magazin: “Dass kritische Infrastruktur über ungesicherte Funknetze kommuniziert, ist ein sicherheitspolitisches Armutszeugnis.” Man öffne Angreifern Tür und Tor, gefährde die Versorgungssicherheit und letztlich Menschenleben, sagte der Sprecher der AG, Thomas Blinn. 
Dem Bericht nach reicht ein Laptop, eine frei verfügbare Software sowie etwas technisches Verständnis, um die Gespräche abzuhören. Dabei könnten auch vertrauliche oder sensible Informationen abgefangen werden. 
Auf Verschlüsselung verzichtet
In Deutschland sind mehr als 300 digitale Funknetze auf Basis des Tetra-Standards aktiv. Das ist eine Technik, auf der auch der Polizeifunk basiert. Dieser ist mehrfach verschlüsselt und gilt als abhörsicher. In mehreren Haftanstalten, Flughäfen sowie bei Energieversorgungseinrichtungen werde jedoch eine Version des Tetra-Netzes eingesetzt, die ohne Verschlüsselung auskomme, schrieb das Magazin und verwies auf Kostengründe. (dpa/jm)

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CSOonline

Jamie Norton’s journey to CISO started with an early interest in computers

Jamie Norton’s parents gave him a computer as a child that he played and tinkered with while growing up. When he went to university, he studied IT and accounting “just as a bit of a side note, really.” This was right around when the internet was emerging, and he started to play with Unix and other operating systems with software development as his background.
When he left university, he didn’t know what he was going to pursue in tech, but the Dotcom boom presented a range of technology opportunities, and his first role was in intelligence for Defence. “And that was where I started to get the mind thinking more in security terms,” he tells CSO of those early days for the department in the tech security space. “But the concepts of risk and the concepts of protecting networks and some of the fundamentals were there.” And that was when Norton first realized that cybersecurity could be a career opportunity.
Around 2000, Norton “formally dropped into” cybersecurity.
“I started out post defence, was on the vendor side and some startups. Went through a period of really strong digital trust systems, authentication, identity and then moved into more mainstream and early cyber leadership roles.” Norton also had several sales roles midcareer, before working his way back to cyber leadership roles with a “return back to consulting more recently.”
His cybersecurity career has included stints with the World Health Organization, NEC Australia, and the Australian Taxation Office. Today he is vice chair of the board of directors at ISACA and the CISO at the Australian Securities and Investments Commission (ASIC).
CSO spoke to Jamie Norton about cybersecurity challenges in finance and government and about retaining talent. Following is that conversation, edited for length and clarity.
What are some of the key challenges that cybersecurity leaders face today?
Norton: Obviously, it’s a very complex space, but at the same time there are foundational things that shift the needle a long way. Part of the challenge for CISOs is how to get that foundational hygiene into organizations. Legacy environments, that’s probably the biggest challenge, particularly in government. Trying to secure systems that are old and out of date, no longer being updated and require significant investment to shift the security posture.
But sitting on top of that is the concept of broad hygiene across the environment, and just doing the basics can be really challenging. There’s a process element to that, there’s obviously a technology element, but then there’s a human element to that as well. So, it’s trying to get all of those bases aligned.
Right now, AI and a whole range of things are emerging that are going to be huge, and we don’t really know what 10 years in from now is going to look like, maybe even five years. Things are changing so rapidly and as technology and security people we want to be innovative and move quickly and be at the forefront of this because otherwise there’s a risk you get left behind. But we must do it in a safe manner so we’re not accidentally exposing sensitive information. That’s a challenge as well.
In your experience as a cybersecurity leader, what does cybersecurity usually mean to organizations?
Norton: It varies. It certainly has changed over time and between organizations. It does depend on size and scale but also a lot depends on the board and the executive security mindset as well. In mid to large government agencies, there’s a real focus on cybersecurity at the executive level. And there’s strong policy and frameworks as well, such as the PSPF [Protective Security Policy Framework] and other frameworks and requirements.
In the corporate space it varies considerably. We’ve seen even some large organizations where it has been a bit of a struggle getting the executives and board functions to accept accountability for security risk. They’re just taking a little bit longer than perhaps others that have been championing security for some time. I think with what’s happening in the market, the broader regulation, the general level of communication around security that’s happening in the media and otherwise, and the incidents is the other thing, the cost of those incidents, like the OPTUS’s and the Medibank’s and Qantas most recently. I think that’s turning that tide with increasing focus on effective cyber governance. I think there’s more and more support emerging at the highest levels of organizations — the executive leadership team and directors — which will enable us to shift the needle even further.
How do you keep your team inspired to prevent cybersecurity professionals from leaving?
Norton: In government, we often don’t have quite the same level of compensation as in the corporate space, so we try to create a positive culture and environment that people love to work in. My personal goal is to provide mentorship and advice to the team while also being very transparent about what career options look like and what the industry is like in different areas. I am my team’s strongest advocate in terms of helping them find their path and achieve career ambitions, whether this is within government or not.
Try to cut red tape. It’s difficult sometimes but try to minimise the impacts of those sorts of things. Training is probably a key lever to give people that advantage and being able to educate and learn further in their careers as well as exposure to some exciting technology.
The mission element in government is also critical. We often attract individuals that are very mission-focused and pursue success that’s bigger than themselves. They’re trying to achieve something for the country or for a certain area of the of the economy. That’s a key outcome we offer.
But equally there’s an element, particularly in the graduate and early career stage that we know we’re often an incubator for the next step in their career. And I think being comfortable with that concept is not a bad thing. Yes, they might come in, we’ll get some great innovation from them for the first three to five years of their careers, they’ll get some training and support from us and then they may go into the private sector for a bit, but they may come back to government later. I think it’s a bit of a push pull across the economy.
Where do you see the role of the cybersecurity leader going?
Norton: Innovations like AI are going to fundamentally impact the role and our day-to-day activities. There’ll be some aspects that won’t change, but there’ll be a lot of aspects that are going to morph and change over the next little while. As an industry, we’re still evolving away from being seen as a purely tech-related function and sitting more naturally alongside the risk function. It’s not happening in every organization, but it’s already happening across financial services. I’m hopeful that we’ll start to see that trend in government, where security sits with the chief operating officer or chief risk officer, depending on the organization, which removes that very tech lens and conflicts that represents.
But the role itself has changed significantly over the last 20-25 years and from a very technical beginnings to now being much more of a C-level interfacing with the board and the executive [suite]. That’s going to continue and we are starting to see a lot more directors with at least some cybersecurity expertise.
What questions should CISOs be asking themselves that they often overlook in securing organizations today?
Norton: I think asking yourself, what visibility do you actually have and how confident are you that your view of things is either the correct view and will still be the correct view in three months?
What are you most and least proud of in your career?
Norton: I feel the work I’m doing with ISACA has real impact and legacy, with an ambitious agenda of industry-wide, global initiatives that we believe will improve the industry for professionals.
In terms of mistakes there’s been lots. I’m in that fail fast and learn category. Government’s not always been in that space, the executive mindset’s a little bit different so it’s fair to say I’ve had my fair share of failures and fair share of presentations that didn’t land. But I think that the messaging really is that: As a CISO, you can’t be perfectly prepared from day one. When you start a role — a significant one or in a midsized organization — you’re going to have to learn to respond and recover and go back again and not always going to impress everyone along the way because sometimes you have to deliver a tough message. A lot of the challenge of being a CISO is building an effective narrative and gaining the trust of your ELT and board, so they are fully invested and you can deliver the difficult messages when needed.
It’s also about building the resilience because it can be lonely at times. Sometimes you’re going to be the one who’s catching flak from some executives because they’re not happy with your message that impacts them. I think that’s why cyber burnout is such a problem. It’s often taking all the body blows and getting to a point where you’re just like “I don’t want to do this anymore.” A lot of that comes back to organizational culture and hopefully having an organization that’s very supportive.
Do you think AI will widen the skills gap or help cybersecurity?
Norton: I think there’s definitely some roles in cyber that will change significantly over the next 5-10 years and some that may diminish. I think it’s going to impact other parts of the economy in a more profound way. From a tech perspective, I think a lot of the data analytics and some of the decision-making support systems will more and more become something that AI supports and begins to automate. So they’ll start off as more decision support systems where we’ll need less humans because we’re able to get the information we need more quickly out of an AI and then slowly but surely, with agentic AI and what’s coming, that will allow them to make simple decisions and then slightly more complex, and then over time, I think we’ll start to replace some roles. I’m optimistic this will propel human workers further up the value chain as well; they’ll be further up from a leadership perspective, maybe deeper from a deeply technical perspective.
Is there any saying that you live by?
Norton: When I was in the Tax Office our commissioner at the time, Chris Jordan, had a branding which was “Do the basics brilliantly” and it’s stuck with me as a general mantra, but it applies so well to security because if you do the basics well you would have such a significant uplift in your cyber capability. You can’t just focus on that alone because there’s a lot of other moving parts. But if you can’t get those basics right, that’s going to provide a lot of protection.
The other one I like, which I guess has helped me well, and I think it’s still true is the futility of “repeating the same thing over and over again, while expecting a different result.” That applies in a lot of things. You’ve got to try and change things up if you’re expecting to get a different result. Yet I see it so often in many facets of life.
Any tips for those wanting to begin a career in cybersecurity?
Norton: For graduates and for early career cyber people we’re aware it is challenging transitioning into early-stage career and getting that first job. I think tenacity and drive is a critical attribute and I’m aware that’s easy for me to say from here. But I do see that those that are persistent, engaged, reach out and grab what they can in a proactive way, they might get knocked down a few times, but you know they’ll continue to learn. They might join ISACA. They might do an early certification to try and get a little competitive advantage. More often than not the relationships formed by networking and getting involved, putting yourself out there, result in opportunity.
At more senior levels it becomes harder. I think it’s that learning process again, making sure that you’ve got a CV that demonstrates that you’re building capability. Understanding your brand and honing it professionally. So, polishing the CV to really reflect what your brand is and what you bring to the table is key. You can’t just throw the same tired CV out and scatter it and hope that something’s going to bite, because that might have worked when we had scarcity but these days there’s too much supply in the market.
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CSOonline

FBI Warns North Korean Hackers Using Malicious QR Codes in Spear-Phishing

The U.S. Federal Bureau of Investigation (FBI) on Thursday released an advisory warning of North Korean state-sponsored threat actors leveraging malicious QR codes in spear-phishing campaigns targeting entities in the country. "As of 2025, Kimsuky actors have targeted think tanks, academic institutions, and both U.S. and foreign government entities with embedded malicious Quick Response (QR)View the full article
Hacker News

Enterprises still aren’t getting IAM right

Despite all the warnings, and constant news of devastating cyberattacks, enterprise users are still cutting corners when it comes to identity and access management (IAM).
Nearly two-thirds (63%) of cybersecurity leaders admit their employees continue to bypass security controls so they can work faster, according to new research by security company CyberArk. Furthermore, enterprises are struggling to establish access policies for emerging AI agents and other agentic tools.
This seems to strongly implicate identity and privilege control as central to operational risk.
“The data points to a cultural pattern where immediate productivity wins often outweigh long‑term security posture,” said  Charles Chu, GM of IT and developer solutions at CyberArk. “It is clear that security is still perceived as something that slows people down.”
Privileged access management inadequate
CyberArk surveyed 500 leaders involved in privileged access management (PAM) in identity and infrastructure roles, including DevOps engineers, security managers, cloud security architects, database managers, site reliability and software engineers, and IT support specialists.
They report that in their organizations:
Just 1% have fully implemented a modern just-in-time (JIT) privileged access model; 91% say at least half of their privileged access is always-on (standard privilege), providing unrestricted, persistent access to sensitive systems; 45% apply the same privileged access controls to human and AI identities; 33% lack clear AI access policies. The research also revealed a growing issue with “shadow privilege,” accounts and secrets that are unmanaged, unnecessary, and unknown to cybersecurity leaders. CyberArk found that 54% of organizations uncover these types of accounts and secrets every week.
This suggests that access ownership is “diffuse,” Chu noted. “If no one feels responsible for continuously pruning and governing privileged access, it naturally accumulates. Added to that is the fact that the majority of organizations (88%) manage multiple identity tools, which “creates confusion about who has authority and which system is the source of truth.”
The riskiest human behaviors
CyberArk identified several of the riskiest human behaviors in access management, including:
Copying credentials into personal password managers, chat apps, or email, because the “official” process is slower. Spinning up cloud resources or test environments with privileged access outside central controls. Using shared admin accounts or recycling similar passwords/tokens across systems and environments. Leaving always-on access in place “just in case,” even when those elevated privileges are only required occasionally. “Employees bypass controls for very human reasons,” Chu acknowledged. “They’re under pressure to move fast, and the security tools that they are required to use are often not user-friendly and conflict with how they actually get work done.”
This leads to ad‑hoc local admin creation, and long‑lived IAM roles and API keys that “no one revisits.”
AI is only exacerbating the problems. Users paste keys, logs, or configuration files into AI tools, unintentionally exposing secrets, Chu noted. AI can also deploy apps and alter systems faster than existing controls can keep up, so engineers tend to work around the controls. Further, AI systems and agents are increasingly acting on behalf of users in ways not yet fully visible to security teams. This makes risky shortcuts even more difficult to detect.
“The net effect is that the gap between what the policy says and what actually happens in production is widening,” said Chu.
Give AI agents unique identities
The bottom line: AI agents operate quite differently than human users. As well being speedier, they work continuously and touch multiple systems and data sets in a single workflow. They present a unique risk because they can very quickly execute large numbers of privileged actions.
With this in mind, security teams should treat AI agents as distinct identities with their own access controls, Chu advised. Every individual agent should be assigned a dedicated identity and credentials, with tightly-scoped permissions for specific systems and data sets. Short-lived tokens should take the place of long-lived keys, and elevated rights should only be granted just in time, and for specific tasks. Further, all actions taken by AI agents should be logged and attributable.
Just as with humans, reduced standing access, better visibility, and strong governance must be “applied explicitly and consistently” to AI, Chu noted.
JIT is hard to implement
JIT is a technique that grants select permissions only when required, for a specific purpose, and for a limited period of time. When users or systems request access, they receive a “time-bound and scope-limited” set of privileges, allowing them perform the required task, then automatically “return to a lower baseline.” Chu explained.
“Every step is logged so that organizations can see who or what has powerful access and why,” he said.
But JIT remains difficult to realize in practice, Chu noted, resulting in a heavy reliance on standing privileges, even as enterprises are fully aware of how risky that practice is.
A number of factors are to blame, he said: IT teams can be hesitant to make changes to legacy systems for fear of disruption, and complex IT environments comprising on-premises infrastructure, multiple clouds, and SaaS applications can complicate implementation. Some teams also worry that JIT can slow down incident response or other routine practices.
Adding to the challenges, existing cybersecurity tools haven’t been designed for highly complex enterprise environments, Chu said. “That combination points to fragmentation: There is plenty of tooling, but not enough unified visibility and control.” .
How enterprises can protect themselves
Today’s enterprises need security that is built around centralized identity, least privilege, and automation, Chu emphasized. This means strong single sign‑on (SSO) with multi‑factor authentication (MFA) and contextual policies; modern secret management for passwords, keys, and tokens for both humans and machines; privileged access capabilities that can issue short‑lived access on demand with full logging; and analytics that stitch together activity across human accounts, service accounts, and AI agents.
From a cultural perspective, organizations should establish clearer ownership of identity and privilege management, shared goals, and top-down messaging around cybersecurity practices, he said.
Also, critically, organizations must adopt tools that easily integrate into existing processes and workflows, thus reducing friction and reducing user workarounds. “The key to effective implementation is to make security as invisible as possible to the user as they do their daily work,” Chu asserted.
This article originally appeared on Computerworld.

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CSOonline

5 Top Cybersecurity-Zertifizierungen: So pushen Sie Ihre CISO-Karriere

Lesen Sie, welche Cybersecurity-Zertifizierungen Ihrer Karriere als CISO einen Schub geben.
Foto: Elnur – shutterstock.com
Zertifizierungen in der Cybersicherheit können das vorhandene Fachwissen hervorheben, die Glaubwürdigkeit erhöhen und Aufstiegsmöglichkeiten eröffnen. Zudem sorgen Cybersecurity-Zertifikate dafür, dass leitende Cybersicherheitsfachkräfte über die sich entwickelnden Bedrohungen auf dem Laufenden bleiben. Darüber hinaus erleichtern sie die Vernetzung und stellen Fähigkeiten im Bereich Compliance und Risikomanagement unter Beweis.
“Zertifizierungen decken alle Cybersecurity-Bereiche und -Fähigkeiten ab – das heißt physische, technische, administrative und betriebliche – bis hin zu einer sehr starken Fokus auf einen bestimmten Hardwarehersteller oder eine bestimmte Art von Technologie, wie zum Beispiel Ransomware”, erklärt Rebecca Herold, IEEE-Mitglied und Gründerin der Beratungsfirma The Privacy Professor.
Doch bevor Sie mit dem Sammeln von Zertifizierungen beginnen, sollten Sie herausfinden, in welchem Bereich der Cybersicherheit Sie arbeiten möchten, rät die Expertin. “Es hat keinen Sinn, eine Zertifizierung anzustreben, die Tätigkeiten abdeckt und Kenntnisse über Fähigkeiten erfordert, die Sie während Ihrer Karriere nie anwenden wollen.”
Laut Herold bieten Cybersecurity-Zertifizierungen folgende Vorteile:
Validierung Ihrer Cybersecurity-Fähigkeiten, da sie sich auf die entsprechenden Zertifizierungen beziehen.
Aufbau Ihrer beruflichen Glaubwürdigkeit, indem Sie zeigen, dass Sie in diesem Bereich bleiben und nicht nur von einer Karriere zur nächsten springen. Arbeitgeber investieren gerne in Mitarbeiter, die langfristig bleiben.
Sie helfen Ihnen, Ihre Karriere schneller voranzutreiben, da viele Unternehmen Kandidaten bevorzugen, die sich die Zeit genommen haben, solche Zertifizierungen zu erwerben.
Sie verschaffen Ihnen Anerkennung für Ihre Fähigkeiten bei anderen in der Branche, was für eine lange und erfolgreiche Karriere wichtig ist.
Sie schaffen die Voraussetzungen für mehr Networking-Möglichkeiten, bei denen Sie noch mehr Wissen erwerben und weitere zukünftige Arbeitsmöglichkeiten finden können.
Sie zeigen, dass Sie die standardisierten Cybersicherheitskonzepte kennen, die Sie durch den Erwerb der einzelnen Zertifizierungsarten erlernen.
Sie beweisen Ihr Engagement für ständiges Lernen, für die Aufrechterhaltung des aktuellen Wissensstand und für die berufliche Weiterentwicklung.
Sie unterstützen auch bei Verhandlungen zu Gehaltserhöhungen.
Folgende fünf Cybersecurity-Zertifizierungen können Ihre Karriere fördern:
1. CISSP – Zertifizierter Fachmann für die Sicherheit von Informationssystemen
Die CISSP-Zertifizierung, die von ISC2, einer internationalen gemeinnützigen Vereinigung, angeboten wird, ist laut William Wetherill, CISO bei DefenseStorm, eine anerkannte Zertifizierung für Fachleute, die ein umfassendes Verständnis von IT-Security-Konzepten und Best Practices nachweisen wollen.
“Die Zertifizierung deckt ein breites Spektrum an Sicherheitsthemen ab. Zum Beispiel Anlagensicherheit, Sicherheitstechnik und Risikomanagement” führt der CISO aus. “Die CISSP-Zertifizierung hat einen höheren Standard, da sie von Sicherheitsexperten umfangreiche Berufserfahrung und eine Empfehlung von einem angesehenen ISC2-CISSP-Inhaber verlangt.”
Die damit erworbenen Fähigkeiten sind laut Wetherill zudem entscheidend für die Entwicklung effektiver Sicherheitsstrategien und die Implementierung von Best Practices in der Rolle eines CISO.
Jay Martin, Security Practice Lead bei Blue Mantis, schließt sich dieser Meinung an: “Wenn Sie Ihre Karriere wirklich auf die nächste Stufe heben wollen, ist die CISSP-Zertifizierung das Nonplusultra”. Und Joe Evangelisto, CISO bei NetSPI, ergänzt, dass CISSP immer noch ein De-facto-Standard in der Branche ist und in allen Stellenbeschreibungen für CISOs aufgeführt ist.
Brian Neuhaus, Americas CTO bei Vectra AI, stimmt zu, dass die CISSP-Zertifizierung für CISOs ganz oben auf der Liste stehen sollte. “Der Besitz eines solchen Zertifikats zeigt, dass ein Sicherheitsexperte mit dem Wissen und den technischen Fähigkeiten ausgestattet ist, die für die Implementierung und Verwaltung erstklassiger Sicherheitsprogramme erforderlich sind”, sagt er.
Obwohl das CISSP-Zertifikat und ähnliche Zertifikate nicht einfach zu erlangen sind, sollten Security-Experten kontinuierlich darauf hinarbeiten, um ihre Karriere effektiv voranzutreiben, so Neuhaus. “Darüber hinaus kann die CISSP-Zertifizierung dazu beitragen, die Aufmerksamkeit von Arbeitgebern bei der Überprüfung von Lebensläufen auf sich zu lenken – und sich von anderen Bewerbern abzuheben”, fügt der Vectra-CTO hinzu.
Voraussetzungen: Um diese Zertifizierung zu erhalten, müssen Sie die Prüfung bestehen und mindestens fünf Jahre kumulative, bezahlte Berufserfahrung in zwei oder mehr der acht Bereiche des ISC2 CISSP Common Body of Knowledge (CBK) vorweisen. Die Vorgabe der fünfjährigen Berufserfahrung kann durch andere Leistungen ersetzt werden.
2. CCSP – Zertifizierter Fachmann für Cloud-Sicherheit
Eine neuere Zertifizierung von ISC2, die laut Sanjay Raja, VP of Product Solutions bei Gurucul entscheidend ist, ist der herstellerunabhängige Certified Cloud Security Professional. “Die weltweit anerkannte CCSP-Zertifizierung weist nach, dass Sie über fortgeschrittenes technisches Fachwissen und Verständnis für die effektive Entwicklung, Überwachung und Sicherung von Daten, Anwendungen und Infrastrukturen in der Cloud verfügen”, erklärt Raja.
“Sie ähnelt der CISSP-Zertifizierung, ist aber stärker auf die Cloud-Sicherheit ausgerichtet – eine gute Wahl für CISOs, die Cloud-Technologien unterstützen oder intensiv nutzen”,.
Voraussetzungen: Um sich für diese Cybersecurity-Zertifizierung zu qualifizieren, müssen Sie die Prüfung bestehen und insgesamt mindestens fünf Jahre Berufserfahrung in der IT haben. Drei Jahre davon müssen im Bereich Informationssicherheit liegen und ein Jahr in einem oder mehreren der sechs Bereiche des ISC2 CCSP CBK. Auch hier kann die Vorgabe der fünfjährigen Berufserfahrung durch andere Leistungen ersetzt werden.
3. Zertifizierter Informationssicherheits-Manager (CISM)
Der Certified Information Security Manager (CISM), der von ISACA angeboten wird, stellt eine weitere wichtige Zertifizierung für CISO dar. Er wurde speziell für Fachleute entwickelt, die für die Verwaltung und Überwachung von Informationssicherheitsprogrammen verantwortlich sind.
“Die CISM-Zertifizierung liefert wichtige Informationen darüber, wie man effektive Informationssicherheitsstrategien entwickelt und implementiert, die mit den Gesamtzielen des Unternehmens übereinstimmen, und deckt gleichzeitig eine breite Palette von Themen ab, wie Risikomanagement, Incident Management und Information Security Governance. Diese sind für die Rolle des CISO von entscheidender Bedeutung “, so Wetherill von DefenseStorm.
Die Zertifizierung vermittelt die notwendigen Fähigkeiten und Kenntnisse, um Geschäftsabläufe und strenge Sicherheitsmaßnahmen in Einklang zu bringen, und konzentriert sich mehr auf Management- und Führungsfähigkeiten, während die CISSP-Zertifizierung eher technisch ausgerichtet ist. “Für CISOs bietet ISACA ebenfalls eine Reihe guter Zertifizierungen an, darunter CISM”, fügt Gurucul-Experte Raja hinzu. Diese Zertifizierung biete eine solide Reihe von Tools und Schulungen zur Verwaltung eines Programms.
Für CISOs, die sich mehr in Richtung Governance, Risiko und Compliance oder Sicherheitsmanagement orientieren, ist der CISM von ISACA sehr zu empfehlen, ergänzt Martin von Blue Mantis.
Voraussetzungen: Um diese Zertifizierung zu erlangen, müssen Sie die Prüfung bestehen, sich innerhalb von fünf Jahren nach Bestehen der Prüfung um die Zertifizierung bewerben und fünf Jahre Berufserfahrung im Bereich Informationssicherheit vorweisen können. Sie müssen mindestens drei Jahre Berufserfahrung im Bereich IT-Security-Management in drei oder mehr der Analysebereiche der Berufspraxis haben. Ausnahmen und Substitutionen sind für das Kriterium fünf Jahre Berufserfahrung zulässig.
4. Zertifizierter Prüfer für Informationssysteme (CISA)
Der Certified Information Systems Auditor ist nach Meinung des DefenseStorm-CISO eine weitere wichtige Zertifizierung. Das ISACA bietet sie für Fachleute an, die für die Prüfung, Überwachung und Bewertung der Informationssicherheit und der Geschäftssysteme ihrer Unternehmen verantwortlich sind.
“Die CISA-Zertifizierung ist weltweit anerkannt und in der IT-Branche hoch angesehen. Sie verlangt von Fachleuten, dass sie ihre Kenntnisse und Fähigkeiten in den Bereichen Informationssicherheitsprüfung, -kontrolle und -sicherung nachweisen”, so Wetherill. “Die CISA-Zertifizierung vermittelt ein umfassendes Verständnis dafür, wie man Schwachstellen und Risiken im Bereich der Informationssicherheit erkennt, analysiert und bewertet.” Diese Fähigkeiten seien für einen CISO unerlässlich, um seine Arbeit effektiv auszuführen und sein Unternehmen vor Cyber-Bedrohungen zu schützen.
“Einige Zertifizierungen, wie zum Beispiel der CISA, eignen sich besser für spezialisierte Sicherheitsaufgaben, wie die eines Wirtschaftsprüfers”, kommentiert Corey Nachreiner, CSO bei WatchGuard Technologies. “Der CISA von ISACA ist hilfreich, wenn Sie sich auf die Prüfung der Cybersicherheit eines Unternehmens konzentrieren.”
Voraussetzungen: Um diese Zertifizierung zu erhalten, müssen Sie die Prüfung bestehen und sich innerhalb von fünf Jahren nach Bestehen der Prüfung um die Zertifizierung bewerben. Außerdem müssen Sie mindestens fünf Jahre Berufserfahrung in der Prüfung, Kontrolle oder Sicherheit von Informationssystemen vorweisen können. Mindestens zwei Jahre davon müssen aus den CISA-Praxisbereichen stammen. Ausnahmen und Substitutionen sind für die fünfjährige Anforderung zulässig.
5. GIAC Strategische Planung, Politik und Führung (GSTRT)
Die GIAC-Zertifizierung für strategische Planung, Politik und Führung, die vom SANS Institute angeboten wird, zeigt, dass Sie über das Wissen und die Fähigkeiten verfügen, um den nächsten Schritt in Ihrer Karriere zu machen, und zwar mit der Fähigkeit, strategische Pläne zu erstellen, die auf das Unternehmen abgestimmt sind, sagt Frank Kim, Fellow am Sans Institute.
“Wenn Sie über die technischen Details hinausgehen müssen, um effektiver mit der Geschäftsleitung und dem Vorstand zu kommunizieren, zeigt diese Zertifizierung, dass Sie wissen, wie man sich an strategischen Zielen ausrichtet, eine Roadmap erstellt, einen Business Case aufbaut, eine Sicherheitsrichtlinie erstellt und Ihr Team zum Erfolg führt”, erklärt er.
Voraussetzungen: Um diese Zertifizierung zu erhalten, müssen Sie eine entsprechende Prüfung bestehen.
Auch in Deutschland besonders gefragt
“Insgesamt sind die oben genannten Zertifizierungen schon sehr sinnvoll”, fasst Ron Kneffel, Vorstandsvorsitzender der CISO Alliance, zusammen. “Alle haben einen starken Bezug zur IT Sicherheit – unabhängig von einem Standard oder einer Norm. Die Zertifizierungen sind auch in Deutschland sehr anerkannt und werden gerade im Konzernumfeld immer wieder als Nachweis der Fachkunde gefordert.”
Es sei wichtig zu wissen, dass Zertifikate zwar nicht zwingend erforderlich sind, um eine Karriere im Bereich der Cybersicherheit zu machen, so Neuhaus. “Aber die darin enthaltenen Informationen können von unschätzbarem Wert sein, um sich in der Branche zurechtzufinden. Der Vectra AI-CTO fügt hinzu: “Daher sind gefragte Talente im Bereich der Cybersicherheit nicht auf die Anzahl der Zertifizierungen beschränkt”. Trotzdem sollten CISOs die anderen Qualitäten, Stärken und Attribute außerhalb der Zertifizierungen nicht aus den Augen verlieren, schließt Neuhaus.
Lesetipp: Das brauchen Sie, um ein „next-gen“ CISO zu werden

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CSOonline

Cisco identifies vulnerability in ISE network access control devices

The latest flaw in Cisco Systems Identity Services Engine (ISE), which could expose sensitive information to an attacker, requires rotation of credentials as well as installation of a patch to correct, says an expert.
Cisco ISE is a network access control platform that enforces access policy and manages endpoints.
There have been more critical holes in Cisco products, acknowledged Paddy Harrington, a senior analyst at Forrester Research, and this one does need a threat actor with administrative privileges to execute and get read access to sensitive information. “However,” he advised senior infosec leaders with Cisco ISE servers, “don’t let these things hang around.”
Before patching, he said, admins should:
rotate ISE credentials for those with existing and approved access; ensure only those who need access have credentials; reduce the number of devices that can access the ISE server; patch as soon as it’s possible to take the server offline. In its notice to customers, Cisco says a vulnerability [CVE-2026-20029] in the licensing features of ISE and Cisco ISE Passive Identity Connector (ISE-PIC) could allow an authenticated remote attacker with administrative privileges to gain access to sensitive information. It isn’t clear why this is called a licensing feature vulnerability. Cisco didn’t respond by deadline when asked for an explanation.
The advisory, which describes the problem as of medium criticality, with a CVSS score of 4.9, says the vulnerability is due to improper parsing of XML that is processed by the web-based management interface of Cisco ISE and Cisco ISE-PIC.
Johannes Ullrich, dean of research at the SANS Institute, said, “Most likely, this is an XML External Entity vulnerability.” External entities, he explained, are an XML feature that instructs the parser to either read local files or access external URLs. In this case, an attacker could embed an external entity in the license file, instructing the XML parser to read a confidential file and include it in the response. This is a common vulnerability in XML parsers, he said, typically mitigated by disabling external entity parsing.
An attacker would be able to obtain read access to confidential files like configuration files, he added, and possibly user credentials. Ullrich also said an ISE administrator may have access to a lot of the information, but they should not have access to user credentials.
The Cisco advisory says an attacker could exploit this vulnerability by uploading a malicious file to the application: “A successful exploit could allow the attacker to read arbitrary files from the underlying operating system that could include sensitive data that should otherwise be inaccessible even to administrators. To exploit this vulnerability, the attacker must have valid administrative credentials.”
Cisco said proof-of-concept exploit code is available for this vulnerability, but so far the company isn’t aware of any malicious use of the hole. 
These days, admin credentials aren’t hard to get, Harrington noted. The “dirty secret that few people want to talk about is across IT and security operations there are so many systems that are left with default credentials.” That’s particularly common, he said, with devices behind a firewall, such as network access control servers, because admins think because they are inside the network they can’t be touched by external hackers. But lots of credentials can be scooped up in compromises of applications where Cisco admins might have stored passwords.
Related content: Cisco warns of three critical ISE vulnerabilities
Coincidentally, today researchers at SCORadar released an analysis of data thefts in 2025. Among other things, it notes that credential theft hit a new high last year. A total of 388 million credentials were stolen from the ten most affected platforms, including Facebook, Google, and Roblox.
This article originally appeared on NetworkWorld.
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CSOonline

iOS 26 Shows Unusually Slow Adoption Months After Release

iOS 26 is showing unusually slow adoption among iPhone users months after release, according to third-party analytics.


Usage data published by StatCounter (via Cult of Mac) for January 2026 indicates that only around 15 to 16% of active iPhones worldwide are running any version of ‌iOS 26‌. The breakdown shows iOS 26.1 accounting for approximately 10.6% of devices, iOS 26.2 for about 4.6%, and the original iOS 26.0 release at roughly 1.1%. In contrast, more than 60% of iPhones tracked by StatCounter remain on iOS 18, with iOS 18.7 and iOS 18.6 alone representing a majority of active devices.

Historical comparisons highlight how atypical this adoption curve appears. StatCounter data from January 2025 shows that roughly 63% of iPhones were running some version of iOS 18 about four months after its release. In January 2024, iOS 17 had reached approximately 54% adoption over a similar timeframe, while iOS 16 surpassed 60% adoption by January 2023.

Based on those figures, ‌iOS 26‌ adoption appears to be running at less than one-quarter of the rate achieved by recent predecessors during the same post-release window. StatCounter derives its estimates from web traffic analytics, tracking operating system versions via page impressions across its global network of participating websites.

In the first week of January last year, 89.3% of MacRumors visitors used a version of iOS 18. This year, during the same time period, only 25.7% of MacRumors readers are running a version of ‌iOS 26‌. In the absence of official numbers from Apple, the true adoption rate remains unknown, but the data suggests a level of hesitation toward ‌iOS 26‌ that has not been seen in recent years.

Unlike many previous releases, ‌iOS 26‌ introduces Liquid Glass as a fundamental visual overhaul, replacing large portions of the traditional opaque interface with translucent layers, blurred backgrounds, and dynamic depth effects across system elements. Upon its announcement at WWDC last year, the redesign received mixed reviews, which could be a contributing factor to hesitation around upgrading.

Likewise, Apple now continues to support older operating systems with security updates, allowing users to remain on iOS 18 without immediate pressure to update or forfeit critical patches. This makes it much easier for users to remain on older software.Related Roundups: iOS 26, iPadOS 26Related Forum: iOS 26
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Who Benefited from the Aisuru and Kimwolf Botnets?

Our first story of 2026 revealed how a destructive new botnet called Kimwolf has infected more than two million devices by mass-compromising a vast number of unofficial Android TV streaming boxes. Today, we’ll dig through digital clues left behind by the hackers, network operators and services that appear to have benefitted from Kimwolf’s spread.
On Dec. 17, 2025, the Chinese security firm XLab published a deep dive on Kimwolf, which forces infected devices to participate in distributed denial-of-service (DDoS) attacks and to relay abusive and malicious Internet traffic for so-called “residential proxy” services.
The software that turns one’s device into a residential proxy is often quietly bundled with mobile apps and games. Kimwolf specifically targeted residential proxy software that is factory installed on more than a thousand different models of unsanctioned Android TV streaming devices. Very quickly, the residential proxy’s Internet address starts funneling traffic that is linked to ad fraud, account takeover attempts and mass content scraping.
The XLab report explained its researchers found “definitive evidence” that the same cybercriminal actors and infrastructure were used to deploy both Kimwolf and the Aisuru botnet — an earlier version of Kimwolf that also enslaved devices for use in DDoS attacks and proxy services.
XLab said it suspected since October that Kimwolf and Aisuru had the same author(s) and operators, based in part on shared code changes over time. But it said those suspicions were confirmed on December 8 when it witnessed both botnet strains being distributed by the same Internet address at 93.95.112[.]59.
Image: XLab.
RESI RACK
Public records show the Internet address range flagged by XLab is assigned to Lehi, Utah-based Resi Rack LLC. Resi Rack’s website bills the company as a “Premium Game Server Hosting Provider.” Meanwhile, Resi Rack’s ads on the Internet moneymaking forum BlackHatWorld refer to it as a “Premium Residential Proxy Hosting and Proxy Software Solutions Company.”
Resi Rack co-founder Cassidy Hales told KrebsOnSecurity his company received a notification on December 10 about Kimwolf using their network “that detailed what was being done by one of our customers leasing our servers.”
“When we received this email we took care of this issue immediately,” Hales wrote in response to an email requesting comment. “This is something we are very disappointed is now associated with our name and this was not the intention of our company whatsoever.”
The Resi Rack Internet address cited by XLab on December 8 came onto KrebsOnSecurity’s radar more than two weeks before that. Benjamin Brundage is founder of Synthient, a startup that tracks proxy services. In late October 2025, Brundage shared that the people selling various proxy services which benefitted from the Aisuru and Kimwolf botnets were doing so at a new Discord server called resi[.]to.
On November 24, 2025, a member of the resi-dot-to Discord channel shares an IP address responsible for proxying traffic over Android TV streaming boxes infected by the Kimwolf botnet.
When KrebsOnSecurity joined the resi[.]to Discord channel in late October as a silent lurker, the server had fewer than 150 members, including “Shox” — the nickname used by Resi Rack’s co-founder Mr. Hales — and his business partner “Linus,” who did not respond to requests for comment.
Other members of the resi[.]to Discord channel would periodically post new IP addresses that were responsible for proxying traffic over the Kimwolf botnet. As the screenshot from resi[.]to above shows, that Resi Rack Internet address flagged by XLab was used by Kimwolf to direct proxy traffic as far back as November 24, if not earlier. All told, Synthient said it tracked at least seven static Resi Rack IP addresses connected to Kimwolf proxy infrastructure between October and December 2025.
Neither of Resi Rack’s co-owners responded to follow-up questions. Both have been active in selling proxy services via Discord for nearly two years. According to a review of Discord messages indexed by the cyber intelligence firm Flashpoint, Shox and Linus spent much of 2024 selling static “ISP proxies” by routing various Internet address blocks at major U.S. Internet service providers.
In February 2025, AT&T announced that effective July 31, 2025, it would no longer originate routes for network blocks that are not owned and managed by AT&T (other major ISPs have since made similar moves). Less than a month later, Shox and Linus told customers they would soon cease offering static ISP proxies as a result of these policy changes.
Shox and Linux, talking about their decision to stop selling ISP proxies.
DORT & SNOW
The stated owner of the resi[.]to Discord server went by the abbreviated username “D.” That initial appears to be short for the hacker handle “Dort,” a name that was invoked frequently throughout these Discord chats.
Dort’s profile on resi dot to.
This “Dort” nickname came up in KrebsOnSecurity’s recent conversations with “Forky,” a Brazilian man who acknowledged being involved in the marketing of the Aisuru botnet at its inception in late 2024. But Forky vehemently denied having anything to do with a series of massive and record-smashing DDoS attacks in the latter half of 2025 that were blamed on Aisuru, saying the botnet by that point had been taken over by rivals.
Forky asserts that Dort is a resident of Canada and one of at least two individuals currently in control of the Aisuru/Kimwolf botnet. The other individual Forky named as an Aisuru/Kimwolf botmaster goes by the nickname “Snow.”
On January 2 — just hours after our story on Kimwolf was published — the historical chat records on resi[.]to were erased without warning and replaced by a profanity-laced message for Synthient’s founder. Minutes after that, the entire server disappeared.
Later that same day, several of the more active members of the now-defunct resi[.]to Discord server moved to a Telegram channel where they posted Brundage’s personal information, and generally complained about being unable to find reliable “bulletproof” hosting for their botnet.
Hilariously, a user by the name “Richard Remington” briefly appeared in the group’s Telegram server to post a crude “Happy New Year” sketch that claims Dort and Snow are now in control of 3.5 million devices infected by Aisuru and/or Kimwolf. Richard Remington’s Telegram account has since been deleted, but it previously stated its owner operates a website that caters to DDoS-for-hire or “stresser” services seeking to test their firepower.

BYTECONNECT, PLAINPROXIES, AND 3XK TECH
Reports from both Synthient and XLab found that Kimwolf was used to deploy programs that turned infected systems into Internet traffic relays for multiple residential proxy services. Among those was a component that installed a software development kit (SDK) called ByteConnect, which is distributed by a provider known as Plainproxies.
ByteConnect says it specializes in “monetizing apps ethically and free,” while Plainproxies advertises the ability to provide content scraping companies with “unlimited” proxy pools. However, Synthient said that upon connecting to ByteConnect’s SDK they instead observed a mass influx of credential-stuffing attacks targeting email servers and popular online websites.
A search on LinkedIn finds the CEO of Plainproxies is Friedrich Kraft, whose resume says he is co-founder of ByteConnect Ltd. Public Internet routing records show Mr. Kraft also operates a hosting firm in Germany called 3XK Tech GmbH. Mr. Kraft did not respond to repeated requests for an interview.
In July 2025, Cloudflare reported that 3XK Tech (a.k.a. Drei-K-Tech) had become the Internet’s largest source of application-layer DDoS attacks. In November 2025, the security firm GreyNoise Intelligence found that Internet addresses on 3XK Tech were responsible for roughly three-quarters of the Internet scanning being done at the time for a newly discovered and critical vulnerability in security products made by Palo Alto Networks.
Source: Cloudflare’s Q2 2025 DDoS threat report.
LinkedIn has a profile for another Plainproxies employee, Julia Levi, who is listed as co-founder of ByteConnect. Ms. Levi did not respond to requests for comment. Her resume says she previously worked for two major proxy providers: Netnut Proxy Network, and Bright Data.
Synthient likewise said Plainproxies ignored their outreach, noting that the Byteconnect SDK continues to remain active on devices compromised by Kimwolf.
MASKIFY
Synthient’s January 2 report said another proxy provider heavily involved in the sale of Kimwolf proxies was Maskify, which currently advertises on multiple cybercrime forums that it has more than six million residential Internet addresses for rent.
Maskify prices its service at a rate of 30 cents per gigabyte of data relayed through their proxies. According to Synthient, that price range is insanely low and is far cheaper than any other proxy provider in business today.
“Synthient’s Research Team received screenshots from other proxy providers showing key Kimwolf actors attempting to offload proxy bandwidth in exchange for upfront cash,” the Synthient report noted. “This approach likely helped fuel early development, with associated members spending earnings on infrastructure and outsourced development tasks. Please note that resellers know precisely what they are selling; proxies at these prices are not ethically sourced.”
Maskify did not respond to requests for comment.
The Maskify website. Image: Synthient.
BOTMASTERS LASH OUT
Hours after our first Kimwolf story was published last week, the resi[.]to Discord server vanished, Synthient’s website was hit with a DDoS attack, and the Kimwolf botmasters took to doxing Brundage via their botnet.
The harassing messages appeared as text records uploaded to the Ethereum Name Service (ENS), a distributed system for supporting smart contracts deployed on the Ethereum blockchain. As documented by XLab, in mid-December the Kimwolf operators upgraded their infrastructure and began using ENS to better withstand the near-constant takedown efforts targeting the botnet’s control servers.
An ENS record used by the Kimwolf operators taunts security firms trying to take down the botnet’s control servers. Image: XLab.
By telling infected systems to seek out the Kimwolf control servers via ENS, even if the servers that the botmasters use to control the botnet are taken down the attacker only needs to update the ENS text record to reflect the new Internet address of the control server, and the infected devices will immediately know where to look for further instructions.
“This channel itself relies on the decentralized nature of blockchain, unregulated by Ethereum or other blockchain operators, and cannot be blocked,” XLab wrote.
The text records included in Kimwolf’s ENS instructions can also feature short messages, such as those that carried Brundage’s personal information. Other ENS text records associated with Kimwolf offered some sage advice: “If flagged, we encourage the TV box to be destroyed.”
An ENS record tied to the Kimwolf botnet advises, “If flagged, we encourage the TV box to be destroyed.”
Both Synthient and XLabs say Kimwolf targets a vast number of Android TV streaming box models, all of which have zero security protections, and many of which ship with proxy malware built in. Generally speaking, if you can send a data packet to one of these devices you can also seize administrative control over it.
If you own a TV box that matches one of these model names and/or numbers, please just rip it out of your network. If you encounter one of these devices on the network of a family member or friend, send them a link to this story (or to our January 2 story on Kimwolf) and explain that it’s not worth the potential hassle and harm created by keeping them plugged in.
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Apple CEO Tim Cook Earned $74.3 Million in 2025

Apple CEO Tim Cook earned $74.3 million in 2025, down slightly from $74.6 million in 2024, Apple said in its annual proxy filing released today.


Cook's earnings included a $3 million base salary that has remained the same since 2016, $57.5 million in stock awards, $12 million in performance-based cash awards, and $1.76 million in other compensation, such as 401(k) contributions, life insurance premiums, vacation cash-out, security expenses, and personal air travel expenses. For efficiency and security purposes, Cook is required by Apple to use private aircraft for both business and personal travel.

Apple set a target compensation of $59 million for Cook, the same as in 2024, but Cook earned above that level through the incentive payouts that executives receive when Apple performs well.

Other key senior Apple executives, including outgoing general counsel Kate Adams, chief operating officer Sabih Khan, and retail and people chief Deirdre O'Brien each earned total compensation packages of around $27 million in 2025. Apple saw a chief financial officer transition in 2025, with former CFO Luca Maestri earning $15.5 million in 2025 and new CFO Kevan Parekh earning $22.5 million.Tag: Tim Cook
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Apple's Annual Shareholders Meeting Will Take Place on February 24

Apple's 2026 shareholders meeting will be held on Tuesday, February 24, at 8:00 a.m. Pacific Time, according to an SEC filing that was released today.


Apple shareholders of record as of January 2, 2026, can attend, vote, and submit questions during the meeting by logging in to Apple's virtual meeting website 15 minutes before it kicks off. A control number included in the Notice of Internet Availability of Proxy Materials that's provided to shareholders is required to join.

At the meeting, shareholders will vote to re-elect the company's board of directors, approve executive compensation, and ratify Ernst & Young LLP as Apple's public accounting firm. There will also be votes on shareholder proposals.

Notably, both board chairman Art Levinson (age 75) and board member Ron Sugar (age 77) are up for re-election, despite a company guideline stating that directors may generally not stand for re-election once they have reached the age of 75. Apple provided the following justification in its proxy statement:Levinson's re-nomination as chairman is notable due to recent speculation around Tim Cook's potential retirement as Apple CEO, a move that would likely see him shift into the board chairman position. It is possible that Levinson's continuation in the role beyond age 75 is intended to also serve as bridge to such time that Cook is ready to assume the chairman role, rather than selecting a new chairman for only a relatively brief time until Cook steps down as CEO.
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Apple Again Tests Background Security Updates in iOS 26.3 and macOS Tahoe 26.3

Apple is once again testing its new Background Security Improvement feature that first rolled out in iOS 26.1, iPadOS 26.1, and macOS Tahoe 26.1. Following a previous test earlier this week, developers and public beta testers who are running iOS 26.3, iPadOS 26.3, or ‌macOS Tahoe‌ 26.3 can now install a second Background Security Improvement update for testing purposes.


Apple says Background Security Improvements provide additional security protections between software updates for Safari, WebKit, and other system libraries.

Background Security Improvements can be installed by going to the Privacy and Security section of the Settings app, scrolling down to Background Security Improvements, and selecting the "Install" option. If "Automatically Install" is toggled on, Background Security Improvements will be automatically installed when they come out with no need to manually install them.

Apple says that users who opt not to install the Background Security Improvements will receive the updates in a standard software update.

Apple previously had a Rapid Security Response update feature for delivering security improvements, but it wasn't used often after it was introduced in iOS 16, and was ultimately phased out in favor of Background Security Improvements. At one point in 2023, there was a Rapid Security Response bug that prevented some websites from displaying properly.

Apple warns that Background Security Updates can result in "rare instances of compatibility issues." Should that occur, the updates may be temporarily removed and enhanced in a subsequent software update.
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Apple Loses Safari Lead Designer to The Browser Company

Apple has lost another senior figure from its Safari team as a lead designer departs for The Browser Company, extending a pattern of high-profile exits from Apple's browser team amid intensifying competition around AI-driven browsing.


Marco Triverio was a lead designer for Safari and has now joined The Browser Company, the developer of the Arc and Dia browsers. The move was confirmed by The Browser Company chief executive Josh Miller in a post on X, marking the latest in a series of hires from Apple's Safari design leadership.

Miller emphasized that Triverio's arrival means The Browser Company has now recruited lead designers from every Safari design era that overlapped with the development timelines of Arc and Dia, roughly spanning 2020 through 2025.



The Browser Company has positioned itself as an alternative to traditional browsers by emphasizing significant new interaction models rather than incremental updates. The apps are often compared to Apple software due to their focus on visual clarity, animation, and user experience design.

Its Arc browser introduced a nontraditional tab system, extensive customization options, and collaborative tools such as shared workspaces and a built-in whiteboard. In 2025, the company introduced Dia, a browser designed around AI-assisted workflows that integrate generative tools, collaborative features, and creative utilities directly into the browsing experience.

For Apple, Triverio's exit adds to a broader pattern of senior staff departures that became more visible throughout 2025.Tag: Safari
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The 2 faces of AI: How emerging models empower and endanger cybersecurity

In my long career of safeguarding digital assets, I’ve seen technology shifts come and go, but nothing compares to the disruptive force of AI and large language models (LLMs). AI is quite literally a double-edged sword when it comes to cybersecurity. The same capabilities that allow us to automate threat detection and write secure code faster are being weaponized by adversaries to create a new generation of cyberthreats. For any CISO or security leader, our primary focus must shift; we are no longer just fighting human adversaries, we are fighting AI-augmented, automated threat agents.
The offensive edge
We are witnessing a drastic reduction in the cost and expertise required for cybercrime. What used to take a skilled human weeks can now be orchestrated by an AI agent in hours, driving what we call cyberthreat inflation.
Self-modifying, evasive malware
More recently, the researchers at Google Threat Intelligence Group (GTIG) identified a disturbing new trend: malware that uses LLMs during execution to dynamically alter its own behavior and evade detection. This is not pre-generated code, this is code that adapts mid-execution.
In June 2025, GTIG identified an experimental malware called PROMPTFLUX, which connects to a commercial LLM API (such as the Gemini API) to request new code-obfuscation and evasion scripts on the fly. This technique, which allows for just-in-time code generation, represents a significant step toward autonomous and adaptive malware.
In another case, GTIG identified PROMPTSTEAL, which was being used by the Russia-linked APT28 group against Ukraine. This malware queries an LLM (the Qwen2.5-Coder model on Hugging Face) to generate reconnaissance commands instead of having them hard-coded.
Some analysis projects that the percentage of all malware detections with an LLM contribution has soared from just 2% in 2021 to a projected 50% by 2025.
The first autonomous espionage campaign
Anthropic recently disclosed a highly sophisticated cyber espionage operation, attributed to a state-sponsored threat actor, that leveraged its own Claude Codemodel to target roughly 30 organizations globally, including major financial institutions and government agencies.
The threat actor manipulated the model into functioning as an autonomous cyber attack agent, which executed 80% to 90% of tactical operations, from reconnaissance and vulnerability discovery to credential harvesting and data exfiltration.
The human operator only stepped in at critical choke points, such as authorizing the progression from reconnaissance to active exploitation. The AI autonomously mapped networks, discovered vulnerabilities and performed post-exploitation activities at machine speed, an unprecedented rate that traditional, human-speed defenses cannot match.
Deepfake-driven financial fraud
On the other hand, generative AI has amplified social engineering through hyper-realistic deepfakes. Deepfake-based scams have skyrocketed, enabling voice and video forgeries that deceive even seasoned professionals. A dramatic example occurred when a Ferrari executive was nearly fooled by a voice-cloned deepfake of the CEO.
Even more recently, an employee at a global design firm was fooled by an AI-generated video call impersonating the company’s CFO and other executives, resulting in a $25 million loss transferred to the fraudsters.
The defensive edge
If adversaries are operating at AI speed, our defenses must too. The silver lining of this dual-use dynamic is that the most powerful LLMs are also being harnessed by defenders to create fundamentally new security capabilities.
Vulnerability detection: From zero-days to autonomous pentesting
LLMs’ semantic code understanding and contextual reasoning offer a significant advantage over traditional, signature-based static analyzers, especially in the discovery of unknown threats before malicious actors find and exploit them.
LLMs have shown extraordinary potential in identifying unknown, unpatched flaws (zero-days). These models significantly outperform conventional static analyzers, particularly in uncovering subtle logic flaws and buffer overflows in novel software. For instance, Google’s Big Sleep project used an LLM to identify a zero-day vulnerability in the critical SQLite database used across the industry.
Another example is XBOW, which is an autonomous AI penetration testing agent that leverages LLMs to simulate real-world attacks the same way a human counterpart would do. XBOW achieved the #1 spot on the HackerOne US Leaderboard, demonstrating that AI can match and, in some benchmarks, surpass expert human hackers in finding a broad range of vulnerabilities (e.g., injection flaws, XSS).
By deploying AI agents like XBOW against our own systems, we can systematically test every endpoint and attack vector. This scales ethical offensive security testing from a periodic audit into an on-demand, pre-production workflow.
On the other hand, Google’s DeepMind has pioneered an AI-powered agent called CodeMender that automatically detects, patches and rewrites vulnerable code to eliminate whole classes of security flaws. This reactive and proactive approach represents a major step forward in defensive automation.
Threat hunting and behavioral analysis
LLMs are transforming threat hunting from a manual, keyword-based search to an intelligent, contextual query process that focuses on behavioral anomalies. By processing and correlating massive, unstructured datasets such as network logs, security incident reports and threat intelligence feeds (OSINT), LLMs gain the contextual understanding necessary to generate high-confidence hypotheses about potential threats.
For example, Google Threat Intelligence with Gemini enhances this process by providing essential contextual grounding with data from multiple sources like VirusTotal and Mandiant to determine, in real-time, which global threat actor tactics, techniques and procedures (TTPs) that are most relevant to a particular industry or organization and prioritize what’s most important from tens of thousands of reports.
Furthermore, Palantir’s AIP (Artificial Intelligence Platform) utilizes LLMs to analyze anomalous user or system behavior across vast data lakes, identifies subtle indicators of compromise that span different systems and suggests a prioritized attack path for the human analyst to investigate.
Governance, compliance and regulation
LLMs also offer a profound scalable solution to managing non-technical risk compliance, privacy and regulatory complexity, which represent significant financial and legal liability. LLMs can be leveraged to shift governance from periodic audits to continuous policy enforcement.
For example, Microsoft’s Compliance Manager can ingest and understand vast amounts of unstructured data, such as internal security policies, legal contracts and external regulatory texts like GDPR or the EU AI Act. It then automatically maps the requirements of one framework to another, dramatically reducing the manual effort needed to prove compliance during an audit.
IBM’s Watsonx applies LLM capabilities for compliance and risk management. For a financial services firm, this might mean the model continuously scans new trading application code to verify that all data handling aligns with HIPAA or PCI DSS before deployment, automatically flagging any deviation from established policy.
Bringing it all together
As AI systems continue to advance from generative models to autonomous agents, their dual-use nature can’t be ignored. The same tools that help defenders accelerate incident response can also empower attackers to craft deepfakes, launch social engineering campaigns and more. This tension isn’t a temporary byproduct of innovation, but it is a structural reality of AI’s rapid evolution.
Ultimately, the challenge isn’t to halt AI progress but to guide it responsibly. That means building guardrails into models, improving transparency and developing governance frameworks that keep pace with emerging capabilities. It also requires organizations to rethink security strategies, recognizing that AI is both an opportunity and a risk multiplier.
In the end, AI’s impact on cybersecurity will be shaped not just by what these systems can do, but by how we choose to use them. The future will belong to those who can harness AI’s defensive power while staying vigilant against its offensive potential.
This article is published as part of the Foundry Expert Contributor Network.
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CES 2026: Productivity Gear, Wireless TVs, and More

CES 2026 runs through tomorrow, but most of the media announcements and events have already taken place and MacRumors videographer Dan Barbera is wrapping things up with our third video highlighting some of the neat tech innovations being demoed on the show floor.

Subscribe to the MacRumors YouTube channel for more videos.
Among the new introductions this week are several from Clicks, the company that previously brought the BlackBerry-like physical Clicks Keyboard to the iPhone. ‌CES 2026‌ is seeing the debut of the Clicks Power Keyboard, a pocket-sized Bluetooth keyboard for all of your devices that includes a 2,150 mAh battery and 5W Qi functionality to allow you to top off your phone if you're running low. There's also the Clicks Communicator, a communication-focused smartphone intended to be carried alongside your main phone.

Wireless TVs are also starting to become a thing, with Displace showing off its latest Displace Pro 2 set and the Displace Hub that can transform your existing TV into a wireless TV with integrated battery.

Popular Apple accessory company OWC has partnered with Strada to showcase a new remote video editing solution that leverages peer-to-peer technology rather than cloud-based storage, while Intricuit is on site to demo its accessory that turns your MacBook into a touchscreen Mac, so you don't need to wait for Apple to launch its rumored touchscreen MacBook Pro later this year or next year.

Dan also checked out Rokid's AI glasses, TDM's headphones that twist into a portable speaker, Antic's electric mini bike, Watchitude's AirTag-compatible watches for kids, and more, so watch the full video for a look at all of these products.

‌CES 2026‌ may be coming to a close, but be sure to check out our news hub where we've collected all of our coverage from the week.Tag: CES 2026
This article, "CES 2026: Productivity Gear, Wireless TVs, and More" first appeared on MacRumors.com

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John Ternus Again Profiled as Apple's Likely Next CEO

With Tim Cook having recently turned 65 years old and a number of other senior Apple executives having already departed in recent months or heading for the exits, there has been significant focus on Apple's plans for who will succeed Cook as CEO.


Several recent reports have identified Apple's senior vice president of hardware engineering, John Ternus, as likely to be named the next Apple CEO, and The New York Times has now shared a profile of Ternus with some context on his expertise and how he is viewed within the company.

According to sources who spoke to The New York Times, Apple began accelerating its planning for ‌Tim Cook‌'s succession last year, with Cook having expressed a desire to reduce his workload.

While software chief Craig Federighi, services chief Eddy Cue, marketing head Greg Joswiak, and retail/HR chief Deirdre O'Brien have all reportedly been seen as potential candidates, Ternus "appears to have shot to the front of the pack," with Cook likely to remain as chairman of the company's board of directors.

Ternus is known for his expertise as an engineer, having worked on many of Apple's devices although he is "known more for maintaining products than developing new ones." Ternus also has only limited exposure to dealing with political and policy issues that come with CEO role.Ternus and others may quibble with that assessment, however, as Ternus has been involved with a number of innovative products over the years, including spearheading the effort to develop the iPhone Air and working on the upcoming foldable iPhone.

Ternus is seen as a natural successor to Cook, with an even temperament, strong attention to detail, and intimate knowledge of Apple's supply chain. But he may not bring the visionary focus and willingness to take risks that Steve Jobs had, leading to debate among Apple employees about exactly what type of leader is needed.

For more on Ternus and his work rising through the ranks at Apple, check out the full profile at The New York Times.Tag: John Ternus
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WhatsApp Worm Spreads Astaroth Banking Trojan Across Brazil via Contact Auto-Messaging

Cybersecurity researchers have disclosed details of a new campaign that uses WhatsApp as a distribution vector for a Windows banking trojan called Astaroth in attacks targeting Brazil. The campaign has been codenamed Boto Cor-de-Rosa by Acronis Threat Research Unit. "The malware retrieves the victim's WhatsApp contact list and automatically sends malicious messages to each contact to furtherView the full article
Hacker News

China-Linked UAT-7290 Targets Telecoms with Linux Malware and ORB Nodes

A China-nexus threat actor known as UAT-7290 has been attributed to espionage-focused intrusions against entities in South Asia and Southeastern Europe. The activity cluster, which has been active since at least 2022, primarily focuses on extensive technical reconnaissance of target organizations before initiating attacks, ultimately leading to the deployment of malware families such as RushDropView the full article
Hacker News

Cybersecurity at the edge: Securing rugged IoT in mission-critical environments

Edge computing is no longer a futuristic concept; it’s a reality shaping mission-critical operations across defense, utilities and public safety. Rugged IoT devices, engineered to withstand extreme conditions, are the backbone of this transformation. They enable real-time decision-making in environments where traditional IT infrastructure cannot survive.
But this progress comes with risk. These devices often operate outside secure perimeters, in disconnected environments and under physical stress. Unlike enterprise systems, rugged IoT deployments break the assumptions of conventional cybersecurity models: stable connectivity, frequent patching and controlled environments.
For CIOs and IT leaders, rugged IoT security isn’t just a technical challenge, it’s a business-critical priority. The cost of failure is measured in millions of dollars, regulatory penalties and reputational damage.
The business stakes
Cybersecurity failures at the edge have cascading consequences. The following examples give a sense of the impact.
Defense: Compromised devices can leak mission-critical data or disrupt tactical communications. Utilities: Operational paralysis halts power distribution or water treatment, impacting millions. Public safety: Emergency response systems fail during crises, endangering lives. According to Gartner, in 2023, IoT-related incidents in critical infrastructure surged 400% over the previous three years and the average cost of an OT breach exceeded $3 million. This excluded reputational damage and compliance fines. For CIOs, this isn’t just about security, it’s about business continuity, compliance and risk management.
Why rugged IoT is different
Securing rugged IoT devices requires a fundamentally different approach than traditional IT systems. Conventional cybersecurity models are built on assumptions that rarely hold true in edge environments.
Traditional IT assumptions:
Stable connectivity: Continuous network access for monitoring and patching. Controlled environments: Secure, climate-controlled data centers. Frequent patching: Regular updates to address vulnerabilities. Centralized monitoring: Unified visibility across systems. Rugged IoT reality:
Harsh conditions: Devices operate at extreme temperatures, dust, moisture and vibration. These conditions accelerate hardware wear and complicate maintenance schedules. Intermittent connectivity: Edge devices often rely on unreliable or low-bandwidth links. Real-time patching and centralized monitoring become impractical, leaving systems exposed for longer periods. Operational constraints: Many rugged devices run unattended for years in remote or hazardous locations. Physical access for updates or repairs is limited, increasing reliance on secure remote workflows. Legacy integration: Rugged IoT frequently coexists with outdated operational technology (OT) systems that lack modern security controls. This creates vulnerabilities at integration points. These factors dismantle the foundation of traditional security strategies. CIOs cannot assume continuous oversight or rapid response capabilities. Instead, rugged IoT demands adaptive, decentralized security architectures that:
Operate effectively in disconnected environments. Combine physical security with cyber protection. Support offline patching and secure update chains. Incorporate zero-trust principles even in bandwidth-constrained scenarios. Standards: Helpful but insufficient
Industry frameworks such as ISA/IEC 62443 and NIST SP 800-82 remain essential for guiding industrial cybersecurity, but their applicability to rugged IoT environments is limited. While these standards provide a strong foundation, they were designed for predictable, connected infrastructures, not for devices operating in remote, harsh and intermittently connected conditions. Standards fall short for rugged IoT in numerous aspects:
Connectivity dependency: Both frameworks assume continuous network availability for monitoring, patching and compliance validation. Rugged deployments often operate offline for extended periods, making real-time adherence impossible. Physical security blind spot: ISA/IEC and NIST primarily address logical and network security layers, leaving physical protection underemphasized. Rugged devices deployed in the field face risks of theft, tampering and environmental damage that these standards do not fully address. Complexity and cost: Full implementation of these frameworks can be resource-intensive, requiring specialized expertise and significant investment. For organizations with constrained budgets or distributed assets, achieving full compliance may be impractical. Static approach vs. dynamic reality: Standards are prescriptive and slow to evolve, while rugged IoT environments demand adaptive strategies that respond to changing operational conditions and emerging threats. Compliance is a starting point, not the finish line. CIOs should adapt these frameworks for edge conditions, integrate physical hardening and prioritize risk-based implementation.
Best practices for CIOs
Securing rugged IoT devices requires a multi-layered, defense-in-depth approach that aligns with enterprise priorities and addresses the unique challenges of edge environments. Each layer plays a critical role in reducing risk and ensuring operational continuity:
1. Device hardening
The foundation of rugged IoT security begins at the device level. Implement secure boot to ensure devices only run trusted firmware by validating cryptographic signatures during startup. Encrypt storage to protect sensitive operational data and credentials from unauthorized access, even if the device is physically compromised. Reduce the attack surface by disabling unused interfaces such as USB or serial ports and turning off unnecessary services. Additionally, schedule periodic firmware integrity checks to detect tampering or unauthorized modifications.
2. Access control
Strong identity and access management are essential for field-deployed devices. Multifactor authentication (MFA) should be required for administrative access, even in low-bandwidth environments, using token-based or offline-capable solutions. Role-based access control (RBAC) aligned with ISA/IEC 62443 principles ensures least-privilege access for technicians, operators and remote administrators.
To further strengthen security, automate credential rotation to prevent password or key reuse across devices.
3. Network security
Connectivity at the edge is often intermittent and insecure, demanding robust network protections. Adopt a zero-trust architecture to authenticate every device and transaction, regardless of network location. Use lightweight VPN protocols optimized for unreliable links to maintain confidentiality without degrading performance. For critical operations, consider secure connectivity options such as FirstNet or private 5G to reduce exposure to public networks.
Additionally, segment IoT traffic from enterprise networks to contain potential breaches and limit lateral movement.
4. Physical security
Cybersecurity must be complemented by physical safeguards to protect devices in harsh environments. Deploy tamper-evident seals to detect unauthorized access attempts quickly and use ruggedized enclosures to shield devices from environmental stressors and physical attacks. Secure mounting reduces theft risk by anchoring devices in fixed installations, while sensor-based alerts, such as accelerometers or intrusion sensors, can trigger notifications when devices are moved or opened.
5. Life cycle management
Security is not a one-time effort; it spans the entire device life cycle. Regular patching and OS hardening are essential to maintain compliance with frameworks like CJIS, FISMA and HIPAA. Develop offline update workflows for disconnected environments, ensuring cryptographic validation of update packages. Strengthen supply chain security by validating firmware and hardware integrity during procurement and deployment to prevent compromised components. Finally, implement secure end-of-life sanitization processes to wipe data and decommission devices safely, preventing residual data leaks.
6. Remote management
Remote capabilities are critical for mitigating risks in inaccessible locations. Enable remote lock and wipe functions to respond immediately to lost or stolen devices, even over intermittent connections. Use centralized management dashboards to maintain visibility into device health, patch status and overall security posture across distributed deployments. Configure automated alerts for anomalies such as unauthorized access attempts or connectivity failures to ensure timely intervention.
Enterprise impact: ROI and risk
As mentioned earlier, investing in rugged IoT security isn’t just a cost; it’s a risk mitigation strategy. CIOs need to consider:
Downtime costs: Utilities report losses of $500,000 per hour during outages, according to the Industrial Control Systems Cyber Emergency Response Team. Regulatory exposure: Non-compliance with CJIS or HIPAA can result in fines exceeding $1 million. Reputation: Public safety failures erode trust and brand equity. For CIOs, the message is clear: Rugged IoT security is not just an IT issue, it’s a business imperative. The cost of inaction is measured not only in dollars but in operational continuity and human safety.
Future outlook
Emerging technologies and developments will further reshape rugged IoT security:
AI-driven anomaly detection for real-time threat identification. Predictive maintenance aligning security patches with hardware health. Regulatory evolution (CISA, EU Cybersecurity Act) enforcing stricter compliance. Forward-thinking CIOs should start integrating these capabilities into their edge strategies today. Rugged IoT deployments are mission-critical and increasingly targeted by cyberthreats. Securing these environments requires a shift from traditional IT models to adaptive strategies tailored for the edge.
This article is published as part of the Foundry Expert Contributor Network.
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Get Up to $199 Off Apple's M5 MacBook Pro on Amazon

Amazon today has dropped the price of the new M5 MacBook Pro to $1,449.00, down from $1,599.00. This is the 10-Core model with 16GB RAM and 512GB SSD, and it's a solid second-best price on the M5 MacBook Pro.

Note: MacRumors is an affiliate partner with some of these vendors. When you click a link and make a purchase, we may receive a small payment, which helps us keep the site running.

Additionally, the 16GB/1TB M5 MacBook Pro has hit $1,599.99 on Amazon, which is a $199 discount on the notebook. Both models have estimated delivery dates around January 13, and right now we're not tracking any deals on the high-end 1TB model.

$150 OFF14-inch M5 MacBook Pro (16GB RAM/512GB) for $1,449.00
$199 OFF14-inch M5 MacBook Pro (16GB RAM/1TB) for $1,599.99

This version of the MacBook Pro launched in October and it comes with the newest M5 chip, which offers up to 15% faster CPU performance and up to 45% faster graphics when compared to the M4 chip. If you're on the hunt for more discounts, be sure to visit our Apple Deals roundup where we recap the best Apple-related bargains of the past week.



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Interested in hearing more about the best deals you can find in 2026? Sign up for our Deals Newsletter and we'll keep you updated so you don't miss the biggest deals of the season!




Related Roundup: Apple Deals
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Phishing-Angreifer setzen vermehrt auf E-Mail-Routing-Lücken

batjaket – shutterstock.com
Das Threat Intelligence Team von Microsoft hat kürzlich festgestellt, dass Angreifer zunehmend komplexe E-Mail-Weiterleitungen und falsch konfigurierte Domain-Spoofing-Schutzmaßnahmen ausnutzen. Dabei lassen sie ihre Phishing-Nachrichten so aussehen, als würden sie von den angegriffenen Organisationen selbst stammen.
In den Angriffskampagnen werden Konfigurationslücken missbraucht. Das gilt insbesondere für solche bei MX-DNS-Einträgen (Mail Exchanger), die nicht direkt auf Microsoft 365 verweisen und in denen die Richtlinien für Domain-based Message Authentication, Reporting & Conformance (DMARC) und Sender Policy Framework (SPF) zu lax oder falsch konfiguriert sind.
„Angreifer haben diesen Vektor genutzt, um eine Vielzahl von Phishing-Nachrichten im Zusammenhang mit verschiedenen Phishing-as-a-Service-Plattformen (PhaaS) wie Tycoon 2FA zu versenden“, erklärt Microsoft in einem Blogbeitrag.
Der Technikriese weist darauf hin, dass dieser Angriffsvektor zwar nicht neu ist, seine Nutzung jedoch seit Mitte 2025 deutlich zugenommen hat. Dabei reichen die Phishing-Köder von Passwort-Zurücksetzungen bis hin zu freigegebenen Dokumenten.
„Internes“ Routing und schwache Richtlinien
Der Fehler liegt darin, wie empfangende Mailserver eingehende Nachrichten interpretieren. Wenn MX-Einträge zu komplexen Mail-pPfaden führen, zum Beispiel zu lokalen Systemen oder Microsoft 365 vorgeschalteten Relay-Servern von Drittanbietern , werden standardmäßige Spoofing-Schutzprüfungen wie SPF Hard-Fail und strenge DMARC-Durchsetzung möglicherweise nicht korrekt angewendet.
In diesen Fällen kann eine Phishing-E-Mail mit der eigenen Adresse des Empfängers sowohl im „An”- als auch im „Von”-Feld ankommen, eine gefälschte Nachricht, die auf den ersten Blick wie eine interne E-Mail erscheint. In einigen Fällen ändern Angreifer zusätzlich den Absendernamen, um die Nachricht überzeugender erscheinen zu lassen, während das „Von”-Feld auf eine gültige interne E-Mail-Adresse gesetzt wird.
In Kombination mit laxen oder fehlenden DMARC- und SPF-Richtlinien können diese Nachrichten Spam-Filter umgehen und direkt im Posteingang der Benutzer landen.
„Phishing-Nachrichten, die über diesen Vektor versendet werden, können effektiver sein, da sie wie intern versendete Nachrichten erscheinen“, betont Microsoft in seinem Beitrag. „Eine erfolgreiche Kompromittierung von Anmeldedaten durch Phishing-Angriffe kann zu Datendiebstahl oder Business Email Compromise (BEC)-Angriffen auf das betroffene Unternehmen oder dessen Partner führen und umfangreiche Abhilfemaßnahmen erforderlich machen und/oder im Falle von Finanzbetrug zu finanziellen Verlusten führen.“
Über die Erfassung von Anmeldedaten hinaus kann die PhaaS-Infrastruktur AiTM-Angriffe (Adversary-in-the-Middle) ermöglichen, bei denen Authentifizierungsinformationen in Echtzeit weitergeleitet werden und sogar Multi-Faktor-Authentifizierungsmaßnahmen umgangen werden können.
Konfigurationen zur Absicherung können helfen
Microsoft betont, dass eine korrekte Konfiguration von E-Mail-Authentifizierungsmechanismen die wirksamste Verteidigung gegen diesen Spoofing-Vektor sei. Unternehmen wird empfohlen, strenge DMARC-Reject-Richtlinien einzuführen und SPF-Hard-Fails durchzusetzen, damit nicht authentifizierte E-Mails, die angeblich von ihren Domänen stammen, abgelehnt oder sicher unter Quarantäne gestellt werden.
Darüber hinaus wird empfohlen, alle Konnektoren von Drittanbietern, wie Spamfilter, Archivierungsdienste oder ältere Mail-Relays, korrekt einzurichten. Damit können Spoof-Prüfungen konsistent berechnet und durchgesetzt werden.
Mandanten mit MX-Einträgen, die direkt auf Microsoft 365 verweisen, sind von diesem Problem nicht betroffen. Die nativen Spoof-Erkennungs- und Filtermechanismen von Microsoft verhindern solche Angriffe und werden standardmäßig angewendet. Für komplexere E-Mail-Infrastrukturen hat Microsoft spezifische Richtlinien zu E-Mail-Regeln und Authentifizierungsverfahren bereitgestellt, um das Risiko zu verringern und gefälschte E-Mails zu blockieren, bevor sie überhaupt den Posteingang der Endbenutzer erreichen.
Über die Korrekturen zur E-Mail-Authentifizierung hinaus fordert Microsoft Unternehmen dazu auf, ihre Identitäts-Schutzmaßnahmen gegen AiTM-Phishing zu verstärken, einer Methode, bei der Passwörter durch die Übernahme authentifizierter Sitzungen umgangen werden. Zu den empfohlenen Kontrollmaßnahmen gehören Phishing-resistente MFA wie FIDO2-Sicherheitsschlüssel, die Durchsetzung bedingter Zugriffsrechte und Schutzmaßnahmen wie MFA-Nummernabgleich, um die Auswirkungen gestohlener Token zu begrenzen. (jm)
View the full article
CSOonline

Phishing-Angreifer setzen vermehrt auf E-Mail-Routing-Lücken

batjaket – shutterstock.com
Das Threat Intelligence Team von Microsoft hat kürzlich festgestellt, dass Angreifer zunehmend komplexe E-Mail-Weiterleitungen und falsch konfigurierte Domain-Spoofing-Schutzmaßnahmen ausnutzen. Dabei lassen sie ihre Phishing-Nachrichten so aussehen, als würden sie von den angegriffenen Organisationen selbst stammen.
In den Angriffskampagnen werden Konfigurationslücken missbraucht. Das gilt insbesondere für solche bei MX-DNS-Einträgen (Mail Exchanger), die nicht direkt auf Microsoft 365 verweisen und in denen die Richtlinien für Domain-based Message Authentication, Reporting & Conformance (DMARC) und Sender Policy Framework (SPF) zu lax oder falsch konfiguriert sind.
„Angreifer haben diesen Vektor genutzt, um eine Vielzahl von Phishing-Nachrichten im Zusammenhang mit verschiedenen Phishing-as-a-Service-Plattformen (PhaaS) wie Tycoon 2FA zu versenden“, erklärt Microsoft in einem Blogbeitrag.
Der Technikriese weist darauf hin, dass dieser Angriffsvektor zwar nicht neu ist, seine Nutzung jedoch seit Mitte 2025 deutlich zugenommen hat. Dabei reichen die Phishing-Köder von Passwort-Zurücksetzungen bis hin zu freigegebenen Dokumenten.
„Internes“ Routing und schwache Richtlinien
Der Fehler liegt darin, wie empfangende Mailserver eingehende Nachrichten interpretieren. Wenn MX-Einträge zu komplexen Mail-pPfaden führen, zum Beispiel zu lokalen Systemen oder Microsoft 365 vorgeschalteten Relay-Servern von Drittanbietern , werden standardmäßige Spoofing-Schutzprüfungen wie SPF Hard-Fail und strenge DMARC-Durchsetzung möglicherweise nicht korrekt angewendet.
In diesen Fällen kann eine Phishing-E-Mail mit der eigenen Adresse des Empfängers sowohl im „An”- als auch im „Von”-Feld ankommen, eine gefälschte Nachricht, die auf den ersten Blick wie eine interne E-Mail erscheint. In einigen Fällen ändern Angreifer zusätzlich den Absendernamen, um die Nachricht überzeugender erscheinen zu lassen, während das „Von”-Feld auf eine gültige interne E-Mail-Adresse gesetzt wird.
In Kombination mit laxen oder fehlenden DMARC- und SPF-Richtlinien können diese Nachrichten Spam-Filter umgehen und direkt im Posteingang der Benutzer landen.
„Phishing-Nachrichten, die über diesen Vektor versendet werden, können effektiver sein, da sie wie intern versendete Nachrichten erscheinen“, betont Microsoft in seinem Beitrag. „Eine erfolgreiche Kompromittierung von Anmeldedaten durch Phishing-Angriffe kann zu Datendiebstahl oder Business Email Compromise (BEC)-Angriffen auf das betroffene Unternehmen oder dessen Partner führen und umfangreiche Abhilfemaßnahmen erforderlich machen und/oder im Falle von Finanzbetrug zu finanziellen Verlusten führen.“
Über die Erfassung von Anmeldedaten hinaus kann die PhaaS-Infrastruktur AiTM-Angriffe (Adversary-in-the-Middle) ermöglichen, bei denen Authentifizierungsinformationen in Echtzeit weitergeleitet werden und sogar Multi-Faktor-Authentifizierungsmaßnahmen umgangen werden können.
Konfigurationen zur Absicherung können helfen
Microsoft betont, dass eine korrekte Konfiguration von E-Mail-Authentifizierungsmechanismen die wirksamste Verteidigung gegen diesen Spoofing-Vektor sei. Unternehmen wird empfohlen, strenge DMARC-Reject-Richtlinien einzuführen und SPF-Hard-Fails durchzusetzen, damit nicht authentifizierte E-Mails, die angeblich von ihren Domänen stammen, abgelehnt oder sicher unter Quarantäne gestellt werden.
Darüber hinaus wird empfohlen, alle Konnektoren von Drittanbietern, wie Spamfilter, Archivierungsdienste oder ältere Mail-Relays, korrekt einzurichten. Damit können Spoof-Prüfungen konsistent berechnet und durchgesetzt werden.
Mandanten mit MX-Einträgen, die direkt auf Microsoft 365 verweisen, sind von diesem Problem nicht betroffen. Die nativen Spoof-Erkennungs- und Filtermechanismen von Microsoft verhindern solche Angriffe und werden standardmäßig angewendet. Für komplexere E-Mail-Infrastrukturen hat Microsoft spezifische Richtlinien zu E-Mail-Regeln und Authentifizierungsverfahren bereitgestellt, um das Risiko zu verringern und gefälschte E-Mails zu blockieren, bevor sie überhaupt den Posteingang der Endbenutzer erreichen.
Über die Korrekturen zur E-Mail-Authentifizierung hinaus fordert Microsoft Unternehmen dazu auf, ihre Identitäts-Schutzmaßnahmen gegen AiTM-Phishing zu verstärken, einer Methode, bei der Passwörter durch die Übernahme authentifizierter Sitzungen umgangen werden. Zu den empfohlenen Kontrollmaßnahmen gehören Phishing-resistente MFA wie FIDO2-Sicherheitsschlüssel, die Durchsetzung bedingter Zugriffsrechte und Schutzmaßnahmen wie MFA-Nummernabgleich, um die Auswirkungen gestohlener Token zu begrenzen. (jm)
View the full article
CSOonline

Gmail Users Can Now Access These Three AI Features Without Paying

Google today made three Gmail AI features free for all personal account holders in the United States, removing the subscription requirement that previously locked them behind its Google AI Pro or Ultra tiers.


"Help Me Write" allows users to enter prompts to draft entire emails from scratch. Like Apple Intelligence's Writing Tools, Help Me Write includes refinement options like Formalize, Elaborate, and Shorten, and users can also apply Polish to messages they've already written. The feature is available on the web, Android, and iOS, and can be accessed by tapping the pen icon with an AI spark badge.

Gmail is also rolling out personalized Suggested Replies, an evolution of Smart Replies that goes beyond generic responses. The feature analyzes conversation context and matches a user's writing tone and style. For example, if a colleague asks about rescheduling a meeting for another day, Suggested Replies can draft an initial response that reflects how the user typically communicates, after which it can be reviewed before sending.

The third newly free feature is AI summaries for long email threads. When opening a lengthy conversation, an AI Overview card may appear at the top with a bulleted summary of points discussed.


All three features are rolling out today to personal account users in the U.S., with global availability coming later.

The changes come amid Google's preview of a new "AI Inbox" feature arriving in the next few months. The redesigned view will appear as a new option alongside the traditional inbox, offering a personalized briefing that surfaces important information without requiring users to open individual messages.

Google's AI Inbox also includes a "Suggested to-dos" section highlighting bills, reminders, and short-term tasks, along with "Topics to catch up on" that provides context for messages that are important but not immediately actionable. The feature is currently available to Trusted Testers and will roll out more broadly later this year, according to Google.Tag: Gmail
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Best Hospitals in Jamaica, Senegal, Italy, Trinidad & Tobago and Peru

Hospital care is deeply shaped by local healthcare systems, population needs, and available resources. While medical science may be universal, the way hospitals deliver care can vary significantly across regions. For patients and families, understanding these differences helps reduce uncertainty and supports better decision-making.
This article offers a patient-centered overview of hospital care in Jamaica, Senegal, Italy, Trinidad & Tobago, and Peru. Rather than listing or ranking hospitals, it explores how care is typically delivered, what patients value most, and where reliable hospital references can be found when deeper research is needed.
What Defines a Reassuring Hospital Experience
Across cultures and healthcare systems, patients consistently describe similar factors when they feel confident in a hospital’s care:
Doctors with experience in treating similar conditions Reliable access to diagnostics and emergency services Clear explanations of procedures and recovery expectations Safe inpatient environments and attentive nursing care Continuity of care beyond discharge Hospitals that perform well in these areas tend to inspire trust regardless of location.
Jamaica: Hospitals Serving Community and Acute Care Needs
Jamaica’s healthcare system relies largely on public hospitals supported by private clinics. Public hospitals often serve wide geographic areas and play a central role in emergency medicine, surgery, maternity services, and general care.
Patients commonly look for hospitals in Jamaica that provide:
Reliable emergency and trauma care Surgical and inpatient services Maternal and newborn care Access to diagnostics and referrals Because demand can be high, hospitals that manage patient flow and communication effectively are especially valued.
A structured overview of leading institutions is available here:
Top hospitals in Jamaica
https://www.bestcosmetichospitals.com/blog/top-20-best-hospitals-in-jamaica/
Senegal: Referral-Based Care with Expanding Capacity
Senegal’s hospital care is centered around major referral hospitals, particularly in urban areas. These hospitals manage complex cases while regional facilities handle general and emergency care.
Patients in Senegal often prioritize hospitals that offer:
Emergency readiness and inpatient stability Access to specialists through referral systems Diagnostic and laboratory support Continuity of care for ongoing treatment As healthcare infrastructure continues to grow, patients increasingly value hospitals that balance accessibility with dependable services.
To explore trusted facilities, refer to:
Top hospitals in Senegal
https://www.bestcosmetichospitals.com/blog/top-20-best-hospitals-in-senegal/
Italy: Coordinated Care and Clinical Specialization
Italy’s healthcare system is well known for its integration of public and private services under a unified framework. Hospitals often collaborate closely with outpatient clinics, specialists, and rehabilitation services.
Patients in Italy frequently seek hospital care for:
Complex surgeries and specialist procedures Oncology and advanced diagnostics Emergency and trauma services Long-term management of chronic conditions Italian hospitals are often appreciated for structured treatment pathways and clinical depth, particularly for complex medical needs.
For a detailed country-wide overview, see:
Top hospitals in Italy
https://www.bestcosmetichospitals.com/blog/top-20-best-hospitals-in-italy/
Trinidad & Tobago: Accessible Hospitals with Broad Services
Trinidad & Tobago’s healthcare system includes government-run hospitals that provide essential services, alongside private hospitals that offer additional flexibility and personalized care.
Patients often choose hospitals in Trinidad & Tobago for:
Emergency and acute medical care Surgical and inpatient treatment Maternity and pediatric services Specialist consultations Hospitals that combine accessibility with efficient scheduling and communication are especially valued by patients.
A curated list of major hospitals can be found here:
Top hospitals in Trinidad & Tobago
https://www.bestcosmetichospitals.com/blog/top-20-best-hospitals-in-trinidad-and-tobago/
Peru: Urban Centers as Hubs for Advanced Care
Peru’s hospital care is largely concentrated in urban centers, where patients have access to advanced diagnostics, specialist services, and surgical treatment. Regional hospitals provide essential and emergency care, with referrals to larger centers when needed.
Patients commonly seek hospitals in Peru for:
Emergency stabilization and inpatient care Diagnostic imaging and laboratory services Surgical procedures Maternal and pediatric health Urban hospitals often play a key role in coordinating care for complex cases.
For a comprehensive overview of trusted facilities, visit:
Top hospitals in Peru
https://www.bestcosmetichospitals.com/blog/top-20-best-hospitals-in-peru/
A Thoughtful Way to Choose a Hospital
When comparing hospitals across different countries, patients can reduce uncertainty by focusing on three practical questions:
Does the hospital regularly treat my condition? Are emergency services and diagnostics available if complications arise? Do doctors and staff communicate clearly about treatment and recovery? Hospitals that address these points tend to deliver safer and more reassuring care experiences.
Closing Reflection
While hospital systems differ across Jamaica, Senegal, Italy, Trinidad & Tobago, and Peru, patients everywhere seek the same outcome: safe, competent, and compassionate care. Understanding how healthcare systems operate — and using reliable hospital references as a starting point — allows patients and families to make informed decisions even in stressful situations.


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Leading Hospitals in Kuwait, Malawi, Indonesia, Laos & Belgium

Hospitals play very different roles depending on where they operate. In some countries, they are part of highly structured national healthcare systems. In others, they serve as critical referral centers for vast populations with limited access to care. For patients and families, understanding these differences is essential when choosing where to seek treatment.
This article offers a measured, patient-focused overview of hospital care in Kuwait, Malawi, Indonesia, Laos, and Belgium. Rather than ranking hospitals, it explains how each country’s system works, what patients typically prioritize, and where to find curated hospital references for further exploration.
What Patients Should Evaluate Before Choosing a Hospital
Across healthcare systems worldwide, patients tend to value the same core elements:
Proven experience with their specific medical condition Access to diagnostics, emergency care, and inpatient support Clear explanations of treatment options and recovery timelines Safe surgical practices and follow-up care Transparent communication around costs and procedures Hospitals that consistently meet these expectations tend to inspire long-term trust.
Kuwait: Well-Resourced Hospitals and Structured Care
Kuwait’s healthcare system benefits from strong public investment and a mix of public and private hospitals. Facilities are generally well equipped, with modern diagnostics, emergency services, and specialist departments.
Patients commonly choose hospitals in Kuwait for:
Cardiovascular and internal medicine care Oncology services Maternity and neonatal treatment Advanced diagnostic evaluations Hospitals in Kuwait often emphasize organized care pathways, which help patients navigate diagnosis, treatment, and follow-up with clarity.
For a curated list of leading institutions, see:
Top hospitals in Kuwait
https://www.bestcosmetichospitals.com/blog/top-20-best-hospitals-in-kuwait/
Malawi: Referral Hospitals as the Backbone of Care
Malawi’s healthcare system relies heavily on central and regional hospitals that act as referral points for surrounding districts. These hospitals are essential for managing emergencies, inpatient care, and surgical treatment.
Patients in Malawi frequently seek hospitals for:
Emergency stabilization General medicine and surgery Maternal and pediatric services Inpatient treatment for acute conditions Because healthcare access can vary widely by region, patients often prioritize hospitals with reliable infrastructure and referral support.
A national overview of major facilities is available here:
Top hospitals in Malawi
https://www.bestcosmetichospitals.com/blog/top-20-best-hospitals-in-malawi/
Indonesia: A Large System with Regional Diversity
Indonesia’s healthcare landscape is extensive and diverse, reflecting the country’s geography and population size. Urban hospitals often provide advanced diagnostics and specialist care, while regional hospitals focus on essential services.
Patients commonly turn to hospitals in Indonesia for:
Diagnostic imaging and laboratory services Surgical and inpatient treatment Emergency and trauma care Long-term disease management Hospital choice in Indonesia is often influenced by location, specialty availability, and urgency of care.
For a country-wide reference of reputable hospitals, visit:
Top hospitals in Indonesia
https://www.bestcosmetichospitals.com/blog/top-20-best-hospitals-in-indonesia/
Laos: Developing Hospital Services with Regional Coordination
Laos continues to expand its hospital network, particularly in urban and provincial centers. While advanced procedures may be limited to larger hospitals, essential medical and surgical care is increasingly accessible.
Patients in Laos typically seek hospitals for:
General inpatient treatment Emergency and trauma care Basic surgical procedures Maternity and neonatal services For complex conditions, hospitals often coordinate referrals to larger facilities or neighboring countries.
An accessible list of key hospitals can be found here:
Top hospitals in Laos
https://www.bestcosmetichospitals.com/blog/top-20-best-hospitals-in-laos/
Belgium: Highly Structured, Patient-Centered Healthcare
Belgium is widely regarded for its comprehensive healthcare system, combining public hospitals, university medical centers, and private clinics. Patients benefit from advanced diagnostics, specialist networks, and strong patient safety standards.
Hospitals in Belgium are often chosen for:
Tertiary and specialist care Complex surgical procedures Oncology and chronic disease management Integrated inpatient and outpatient services Belgium’s system emphasizes clinical quality, accessibility, and continuity of care, supported by a well-established insurance framework.
For a detailed national shortlist, refer to:
Top hospitals in Belgium
https://www.bestcosmetichospitals.com/blog/top-20-best-hospitals-in-belgium/
A Simple Decision Framework for Patients
When evaluating hospitals across countries, patients can simplify their decision by asking:
Does the hospital regularly treat my condition? Are emergency services, diagnostics, and ICU support available? Are treatment steps and expectations clearly explained? Hospitals that meet these criteria are generally dependable, regardless of system size or location.
Final Reflection
Hospital care varies widely across Kuwait, Malawi, Indonesia, Laos, and Belgium, shaped by economic resources, geography, and healthcare policy. Yet across all five countries, patients can find reliable hospitals by focusing on experience, preparedness, and communication rather than reputation alone.
Using curated hospital lists as a starting point—and understanding how systems function—allows patients to move forward with confidence when healthcare decisions matter most.

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Evaluating Hospital Care Across Lebanon, Morocco, Nepal, Uganda & Nigeria

When people search for hospitals, they are often seeking reassurance more than information. The reassurance that care will be safe, doctors experienced, and decisions transparent. As healthcare options expand globally, patients increasingly compare hospitals across borders—either for access, affordability, specialization, or long-term treatment planning.
This article provides a clear, patient-centric overview of hospital care in Lebanon, Morocco, Nepal, Uganda, and Nigeria. Rather than overwhelming readers with names and rankings, it focuses on how healthcare systems function, what patients can realistically expect, and how to approach hospital selection thoughtfully.
What Patients Should Focus on First
Across countries and healthcare systems, the most reliable hospitals tend to share common characteristics. Patients consistently value:
Experience treating specific conditions Availability of diagnostics and emergency backup Clear explanations of treatment options Safe inpatient and surgical environments Ethical and predictable billing practices These fundamentals matter far more than branding or location alone.
Lebanon: Specialist-Driven Care with Regional Reach
Lebanon has long been recognized for its strong medical education and specialist-driven healthcare. Hospitals in Beirut and other major cities attract patients seeking detailed diagnostics, advanced procedures, and second opinions.
Patients often choose hospitals in Lebanon for:
Cardiology and cardiovascular surgery Oncology and long-term cancer care Complex diagnostic evaluation Surgical specialties with experienced teams Hospitals in Lebanon generally emphasize personalized consultations and careful treatment planning, which many patients find reassuring when managing complex conditions.
For a structured overview of leading institutions, refer to:
Top hospitals in Lebanon
https://www.bestcosmetichospitals.com/blog/top-20-best-hospitals-in-lebanon/
Morocco: Expanding Infrastructure and Urban Excellence
Morocco’s healthcare system has grown steadily, especially in urban centers where both public and private hospitals continue to modernize. Patients benefit from improving diagnostics, surgical capability, and organized inpatient services.
Hospitals in Morocco are frequently selected for:
General and emergency medical care Surgical procedures with modern support Maternal and pediatric services Diagnostic imaging and laboratory services In Morocco, patients often prioritize facility readiness and response time, particularly for planned procedures and inpatient care.
For a national reference list, see:
Top hospitals in Morocco
https://www.bestcosmetichospitals.com/blog/top-20-best-hospitals-in-morocco/
Nepal: Centralized Advanced Care with Regional Support
Nepal’s hospital care is concentrated around major cities, particularly Kathmandu, where private and teaching hospitals offer advanced diagnostics and specialist services. For complex conditions, patients typically rely on these centralized facilities.
Common reasons patients seek hospitals in Nepal include:
Orthopedic and trauma treatment Internal medicine and surgical care Emergency services with diagnostic backup Maternity and neonatal care In Nepal, hospitals that combine emergency preparedness with diagnostic accuracy are often considered the most dependable.
To explore trusted institutions, refer to:
Top hospitals in Nepal
https://www.bestcosmetichospitals.com/blog/top-20-best-hospitals-in-nepal/
Uganda: Referral-Based Care and Regional Hospitals
Uganda’s healthcare delivery is built around major referral hospitals supported by regional and private facilities. These hospitals handle a wide range of cases, from emergency stabilization to complex inpatient treatment.
Patients commonly depend on hospitals in Uganda for:
Emergency and trauma response General surgery and inpatient management Diagnostic and referral services Chronic disease management Because referral hospitals serve large populations, system reliability and continuity of care are key considerations when selecting treatment centers.
For a curated national overview, see:
Top hospitals in Uganda
https://www.bestcosmetichospitals.com/blog/top-20-best-hospitals-in-uganda/
Nigeria: High-Volume Care and Specialist Diversity
Nigeria has one of the most extensive healthcare systems in Africa, combining large teaching hospitals with private and specialty-focused institutions. Major cities host hospitals capable of handling complex, high-volume cases across multiple specialties.
Patients frequently choose Nigerian hospitals for:
Specialist and tertiary care Emergency and trauma services Surgical treatment and diagnostics Maternal, pediatric, and internal medicine services The strength of Nigeria’s system lies in clinical exposure through scale, which builds deep experience in managing complex medical conditions.
For a country-wide shortlist of trusted facilities, visit:
Top hospitals in Nigeria
https://www.bestcosmetichospitals.com/blog/top-20-best-hospitals-in-nigeria/
A Simple Approach to Hospital Selection
Instead of comparing dozens of hospitals, patients can narrow choices by asking:
Does this hospital regularly treat my condition? Are emergency, ICU, and diagnostics available if complications occur? Are treatment plans, timelines, and costs explained clearly? Hospitals that meet these criteria are generally reliable, regardless of geography.
Final Perspective
Healthcare quality is shaped by experience, systems, and transparency—not by borders. Across Lebanon, Morocco, Nepal, Uganda, and Nigeria, patients can find dependable hospitals when they approach the decision with clarity and realistic expectations.
Understanding how healthcare systems operate and using trusted reference lists as starting points allows patients to move forward with confidence rather than uncertainty.

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A Patient’s Guide to Trusted Hospitals in Pakistan, Zambia, Philippines, Sri Lanka & Ghana

Choosing a hospital is one of the most important decisions a patient or family can make. The choice affects not only treatment outcomes, but also emotional comfort, financial clarity, and recovery experience. As healthcare access expands globally, many patients now explore hospitals beyond their immediate region—either for better expertise, affordability, or availability.
This guide offers a clear, patient-focused overview of hospital quality across Pakistan, Zambia, the Philippines, Sri Lanka, and Ghana. Instead of overwhelming you with names and links, the focus here is on how healthcare works in each country, what patients typically look for, and where to find trusted hospital shortlists when deeper research is needed.
What Makes a Hospital “Trusted” in Real Life?
Patients often assume the “best” hospital means the biggest building or the most advertising. In reality, trust is built through consistency and outcomes. Across countries, reliable hospitals usually share these qualities:
Experienced specialists in core departments Strong diagnostic support (labs, imaging, ICU backup) Clear communication with patients and families Safe surgery and infection-control practices Ethical billing and transparent estimates With this lens, let’s look at how each country compares.
Pakistan: Large-Scale Care with Strong Specialization
Pakistan has one of the largest healthcare systems in South Asia, serving millions of patients annually through both public and private hospitals. Major cities host institutions that handle everything from emergency trauma to complex cancer care.
Patients commonly choose hospitals in Pakistan for:
Cardiac care and heart surgery Oncology and long-term treatment Emergency and trauma services Maternal and pediatric care The strength of Pakistan’s system lies in high patient volume, which creates deep clinical experience, particularly in tertiary care centers.
For a carefully curated country-wide shortlist, see:
👉 Best hospitals in Pakistan
Zambia: Improving Access and Urban-Centered Excellence
Zambia’s healthcare system is developing steadily, with the strongest hospitals concentrated in urban regions. Many facilities serve as referral centers for surrounding areas, making them critical to national healthcare delivery.
Patients typically look for hospitals in Zambia when they need:
Dependable emergency services General surgery and inpatient care Diagnostic clarity for chronic conditions Maternal and newborn services When selecting a hospital in Zambia, proximity, emergency readiness, and physician availability matter more than luxury infrastructure.
A helpful comparison list is available here:
👉 Best hospitals in Zambia
Philippines: Private Hospital Networks and Specialized Care
The Philippines has a well-established private healthcare sector alongside public hospitals. Many patients value the system for its organized outpatient care, specialist access, and modern diagnostics.
Hospitals in the Philippines are often chosen for:
Specialized medical consultations Surgical procedures with short wait times Preventive health screenings Long-term disease management The system is particularly patient-friendly for planned treatments, where scheduling and follow-up are essential.
For a reliable national overview, refer to:
👉 Best hospitals in the Philippines
Sri Lanka: Strong Public Foundations with Private Flexibility
Sri Lanka is often noted for its balanced healthcare model. Public hospitals handle a high volume of patients and complex cases, while private hospitals provide faster access, comfort, and convenience.
Patients usually select Sri Lankan hospitals for:
General medicine and surgery Maternity and pediatric services Affordable yet dependable treatment Efficient private hospital care for non-emergency needs The country’s healthcare strength lies in clinical discipline and continuity of care.
For an easy-to-navigate hospital list, see:
👉 Best hospitals in Sri Lanka
Ghana: Teaching Hospitals and Focused Specialty Centers
Ghana’s healthcare system is anchored by major teaching hospitals, supported by a growing number of private and specialty-focused institutions. These hospitals play a critical role in advanced diagnostics, surgery, and referral care.
Patients often seek hospitals in Ghana for:
Emergency and trauma care Surgical procedures Specialist consultations Structured inpatient management Teaching hospitals, in particular, bring together experienced clinicians and multidisciplinary teams.
To explore trusted options across the country:
👉 Best hospitals in Ghana
How Patients Should Make the Final Choice
Rather than searching endlessly, patients can narrow decisions using three questions:
Is this hospital experienced in my exact condition? Do they clearly explain treatment steps and costs? Is emergency or ICU support available if complications arise? If the answer is “yes” to all three, the hospital is usually a safe choice—regardless of country.
Conclusion: Informed Choices Lead to Better Outcomes
Healthcare quality is no longer limited by geography. Across Pakistan, Zambia, the Philippines, Sri Lanka, and Ghana, patients can find hospitals that deliver reliable, ethical, and effective care when they know where to look.
By understanding how each system works and using curated hospital lists as a starting point, patients and families can make decisions with confidence rather than urgency.

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Generate Apple Music Playlists With ChatGPT

Apple Music is now available as an extension within ChatGPT, meaning you can search for songs, create playlists, and discover new music through OpenAI's chatbot. Here's how to set it up and what makes it worth using.


What You Can Do With Apple Music in ChatGPT

ChatGPT's integration with Apple Music has the potential to change how you discover new music by letting you describe what you're looking for in natural language. Instead of typing specific search terms like you would in Apple Music, you can ask the chatbot for "upbeat 80s songs for a road trip" or "calm instrumental music for studying," and ChatGPT will understand the context and mood you're after.

You can even combine multiple criteria, like "jazz fusion tracks under five minutes with prominent saxophone," and ChatGPT will accurately unearth what you're looking for in ways that standard keyword searches simply aren't capable of achieving.


You can request custom playlists based on specific criteria, ask for song recommendations, or explore music by decade, genre, or artist. And once ChatGPT creates a playlist, you can preview each track, and save the playlist directly to your Apple Music library with the option "Create Playlist in Apple Music." You can also save individual tracks using the + buttons.

The Apple Music extension requires a ChatGPT account and works with both free and paid ChatGPT tiers. You don't need an Apple Music subscription to search the catalog, generate playlists, or listen to 30-second preview clips, but you will need an active subscription if you want to save content to your library.

How to Connect Apple Music to ChatGPT

Before you can start discovering new music with the help of AI, you'll need to connect Apple's streaming service using ChatGPT's extension. You only need to do it once.

Open the ChatGPT app and tap your profile in the sidebar.
Under "Account" settings, tap Apps.
Tap Browse Apps, then choose Apple Music in the extensions library.
Tap Connect, then choose Connect Apple Music.
Follow the on-screen prompts to sign into your Apple Account and permit the access request.

If you're on desktop, you can perform the same steps in the ChatGPT app for Mac. Alternatively, go to https://chatgpt.com/apps in a browser and open the Apps section in ChatGPT – you'll find the Apple Music extension there. Once connected, the extension remains active across your devices signed into the same ChatGPT account.

One More Thing

Apple Music extension in ChatGPT's "Apps" section
ChatGPT can search Apple Music's catalog and create playlists, but it can't access your listening history or existing playlists. The integration only has permission to add songs to your library, so your personal data stays private. Tags: Apple Music, ChatGPT
This article, "Generate Apple Music Playlists With ChatGPT" first appeared on MacRumors.com

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ThreatsDay Bulletin: RustFS Flaw, Iranian Ops, WebUI RCE, Cloud Leaks, and 12 More Stories

The internet never stays quiet. Every week, new hacks, scams, and security problems show up somewhere. This week’s stories show how fast attackers change their tricks, how small mistakes turn into big risks, and how the same old tools keep finding new ways to break in. Read on to catch up before the next wave hits. Honeypot Traps Hackers Hackers Fall forView the full article
Hacker News

The State of Trusted Open Source

Chainguard, the trusted source for open source, has a unique view into how modern organizations actually consume open source software and where they run into risk and operational burdens. Across a growing customer base and an extensive catalog of over 1800 container image projects, 148,000 versions, 290,000 images, and 100,000 language libraries, and almost half a billion builds, they can seeView the full article
Hacker News

NIS2-Umsetzung: Neues BSI-Portal geht an den Start

ImageFlow – shutterstock.com
Seit Anfang Dezember gilt die EU-Sicherheitsrichtline NIS2 auch in Deutschland. Rund 29.500 Unternehmen sind dadurch verpflichtet, sich als NIS-2-Einrichtungen zu registrieren und dem Bundesamt für Sicherheit in der Informationstechnik (BSI) erhebliche Sicherheitsvorfälle zu melden. Vor diesem Hintergrund hat das BSI ein neues Portal entwickelt, das gebündelte Informationen und Hilfestellungen bietet.
BSI-Portal soll Austausch erleichtern
Das BSI-Portal basiert auf einer Cloud-Infrastruktur von Amazon Web Services (AWS) und soll sukzessiv zu einer Informations- und Austauschplattform mit Echtzeit-Daten und aktuellen Analysen für schnelle Reaktionsmöglichkeiten ausgebaut werden.
„NIS2 sorgt dafür, dass wichtige und besonders wichtige Einrichtungen sowie die gesamte Bundesverwaltung ihre Cyberresilienz effektiv und effizient stärken. Um diesen und weitere Prozesse komfortabel und unbürokratisch zu gestalten, haben wir das BSI-Portal als One-Stop-Shop konzipiert“, erklärt BSI-Präsidentin Claudia Plattner. „Es soll den sicheren und zielgerichteten Austausch relevanter Cybersicherheitsinformationen zwischen Unternehmen, Behörden und Institutionen erleichtern.“
Das Portal unterstützt Unternehmen unter anderem dabei, eine Risikoanalyse durchzuführen und Maßnahmen zum Risikomanagement umzusetzen. Zudem erhalten bereits registrierte Unternehmen und Institutionen ab sofort Informationen zu ihren gesetzlichen Pflichten.
Zudem können sich Organisationen über die Plattform der Allianz für Cyber-Sicherheit (ACS) anschließen. Das IT-Sicherheits-Netzwerk unter dem Dach des BSI bietet seinen derzeit knapp 9.000 Mitgliedern vielfältige Formate zum Wissens- und Erfahrungsaustausch.
Darüber hinaus stellt das BSI seine Tageslageberichte und IT-Sicherheitsmitteilungen über die Plattform bereit. Auch Schwachstellen und Sicherheitslücken können über das BSI-Portal gemeldet werden – dies ist auch anonym und ohne Registrierung möglich, verspricht die Behörde.
Kritik aus der Security-Szene
Die Tatsache, dass das BSI-Portal auf AWS gehostet wird, sorgt allerdings bei einigen Security-Experten für Unmut. Auf LinkedIn bezeichnet Benjamin Richter, CEO bei Cyber Complete, das Ganze vor dem Hintergrund der digitalen Souveränität als strategisches ein Eigentor.
Der IT-Sicherheitsexperte Jürgen Mayershofer stimmt dem zu: „Das ist ein ganz falsches Signal des BSI an den deutschen Markt, während quer durch Europa über digitale Souveränität und Resilienz diskutiert wird.“
Auch Karsten Bartels, Rechtsanwalt für IT-Sicherheitsrecht, kann die Entscheidung des BSI für AWS nur schwer nachvollziehen. „Gerade diese Plattform dieser Behörde“, moniert der Experte.
„Ganz einfach, BSI steht für ‚Bundesamt für SICHERHEIT in der Informationstechnik‘, nicht “Bundesamt für Souveränität in der Informationstechnik‘“, spöttelt der auf Cloud und Datensouveränität spezialisierte Gartner-Analyst René Büst. „Und Sicherheit und Souveränität haben miteinander nichts zu tun. Man kann eine sehr sichere Cloud nutzen aber gleichzeitig zu 0% souverän sein. Das hat das BSI leider nicht verstanden.“
Lesetipp: NIS2 umsetzen – ohne im Papierkrieg zu enden
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CSOonline

Critical jsPDF vulnerability enables arbitrary file read in Node.js deployments

A now-fixed critical flaw in the jsPDF library could enable attackers to extract sensitive files from enterprise servers and embed them directly into generated PDF documents.
Tracked as CVE-2025-68428, the flaw affects unpatched Node.js deployments of jsPDF, where untrusted input is passed to file-handling APIs without proper validation.
According to an Endor Labs analysis, the issue enables path traversal and local file inclusion, allowing an attacker to read arbitrary files from the underlying filesystem. In affected environments, this could expose credentials, configuration files, private keys, or environment variables.
The vulnerability impacts jsPDF versions 3.0.4 and earlier, specifically the Node.js builds used in server-side PDF generation workflows, and does not affect browser-only usage.
While a fix has been made available, Endor researchers warned that remediation goes beyond a simple version bump, particularly in production environments that rely on dynamic file handling. “The patch provides no protection if the runtime permits unrestricted filesystem access,” Endor researchers said in a blog post.
PDF library turns into a file exfiltration vector
The CVE-2025-68428 issue lies in how jsPDF handles file paths when loading external resources in Node.js. Several commonly used APIs, including “addImage”,“html”, and “addFont”, internally rely on a “loadFile()” function to read files from disk. Prior to version 4.0.0, these methods did not adequately validate or restrict file paths supplied at runtime.
If an application accepts user-controlled input, such as a filename, image path, or font reference, and passes it directly into these APIs, an attacker could supply a crafted path to reference sensitive application files. jsPDF would then read the file and embed its contents into the resulting PDF without triggering an error.
Because the library does not enforce file-type restrictions at this stage, the issue is not limited to images or fronts. Any file readable by the Node.js process can potentially be included.
The bug has been assigned a critical severity rating at a base CVSS score of 9.2 out of 10. Researchers urged upgrading to the fixed version immediately to protect against exploitation.
Patching may not be enough
The jsPDF maintainers addressed the issue in version 4.0.0 by restricting filesystem access by default. The fix relies on Node.js permission mode, which requires applications to explicitly grant read access to specific directories at runtime. When properly configured, this prevents jsPDF from accessing files outside approved paths.
However, this approach introduces operational complexity. Node.js permission mode is evolving, and many production environments either run older Node versions or have not adopted permission-based execution. “Many environments run older Node.js versions that lack stable permission mode support, and enabling –permission may break existing functionality if filesystem access patterns haven’t been carefully mapped,” the researchers noted.
The researchers outlined a set of steps to assess the exploitability of their deployments, which includes verifying if jsPDF is being used server-side ( as it is unexploitable on the client side), checking if the running version already implements permission mode and has filesystem permission properly configured, identifying affected code paths with SCA tools, and manual searching of the vulnerable codebase.
Endor Labs credited security researcher Kwangwoon Kim (KilkAt) for identifying and reporting the vulnerability on GitHub.
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CSOonline

10 Reasons to Wait for This Year's iPhone 18 Pro

Apple's iPhone development roadmap runs several years into the future and the company is continually working with suppliers on several successive iPhone models at the same time, which is why we often get rumored features months ahead of launch. The iPhone 18 series is no different, and we already have a good idea of what to expect for the iPhone 18 Pro and iPhone 18 Pro Max.


One thing worth noting is that Apple is reportedly planning a major change to its iPhone release cycle this year, adopting a two-phase rollout starting with the iPhone 18 series. That means the iPhone 18 Pro, iPhone 18 Pro Max, and iPhone Fold will be released in September 2026, followed by the iPhone 18 and iPhone 18e in spring 2027.


Overall Design

iPhone 17 Pro Style

Rumors suggest the iPhone 18 Pro lineup will largely retain the same design as the iPhone 17 Pro models. The rear camera system will look identical to the current generation, featuring a raised "plateau" with three lenses arranged in a triangle. Display sizes are also expected to remain unchanged, with the iPhone 18 Pro and iPhone 18 Pro Max continuing to use 6.3-inch and 6.9-inch panels, respectively – the same dimensions introduced with the iPhone 16 Pro series. iPhone 18 Pro models could drop the current two-tone look of the rear casing found on the iPhone 17 Pro in favor of a more seamless aesthetic. For the next-generation models, Apple has apparently updated the back-glass "replacement process" to minimize the color difference between the Ceramic Shield 2 glass and the aluminum frame, resulting in a more unified appearance.

Thicker Chassis

Bigger Battery?

According to one rumor, the body of the iPhone 18 Pro Max will be slightly thicker than the iPhone 17 Pro Max, raising the device's weight to around 243 grams. That would make the iPhone 18 Pro Max approximately 3 grams more than the iPhone 14 Pro Max, which is currently the heaviest model Apple has produced. We don't know the exact reason for the alleged thicker design of the iPhone 18 Pro Max, but a larger battery is the most likely cause.

Smaller Dynamic Island

Under-Screen Face ID?

Rumors continue to circulate about whether the iPhone 18 Pro models will introduce under-display Face ID, but reports remain divided on when the technology will actually arrive. The feature would move the TrueDepth camera system beneath the display, eliminating the need for the current Dynamic Island cutout.

According to Wayne Ma of The Information, Apple is targeting a design without a Dynamic Island, replacing it with a single pinhole camera in the upper-left corner of the screen. However, other sources dispute that claim. Display analyst Ross Young believes under-display Face ID is possible for the iPhone 18 Pro, but says a smaller Dynamic Island will still be present. Bloomberg's Mark Gurman has echoed this view, reporting that the new models will feature a slimmed-down Dynamic Island rather than removing it entirely. Apple is also said to be testing new camera miniaturization technology to reduce the size of the front-facing camera currently located within the Dynamic Island.

Meanwhile, Chinese leaker Instant Digital has offered yet another version of events, saying the Dynamic Island will shrink in size, but that under-display Face ID and camera technology won't debut next year. Overall, the consensus suggests Apple may be refining the Dynamic Island before fully transitioning to an all-screen design in future generations.

A20 Pro Chip

2nm Process

The iPhone 18 Pro models will use Apple's A20 chip, based on TSMC's 2nm process for power and efficiency improvements. A move to 2nm fabrication increases transistor density, which will enable higher performance. The A20 series is expected to deliver roughly a 15 percent speed gain and about 30 percent better efficiency compared with the A19 series used in Apple's iPhone 17 models.

Apple's A20 chip will be packaged with TSMC's Wafer-Level Multi-Chip Module (WMCM) technology, suggesting at least some A20 chips will have RAM integrated directly onto the same wafer as the CPU, GPU, and Neural Engine, rather than sitting adjacent to the chip and connected via a silicon interposer. This could contribute to faster performance for both overall tasks and Apple Intelligence, and longer battery life from improved power efficiency.

C2 Modem

Replacing Qualcomm

Apple plans to include its next-generation C2 modem in the iPhone 18 Pro models, according to supply chain analyst Jeff Pu. The chip will succeed the C1 modem, which debuted in the lower-cost iPhone 16e as Apple's first in-house cellular modem, and the C1X modem chip in the iPhone Air, which Apple says is up to 2× faster than the C1. The C2 is expected to bring faster speeds, improved power efficiency, and support for mmWave 5G in the United States – a feature missing from the C1 and C1X.

Apple's modem roadmap is part of a long-term strategy to reduce reliance on Qualcomm, which currently supplies 5G modems for the rest of the iPhone lineup. The company has been working on developing its own cellular chips for years, aiming for deeper integration and greater control over power management and performance.

New Camera Sensor

Samsung-Made

Samsung is working on a new three-layer stacked image sensor, reportedly intended for the iPhone 18. The sensor, referred to as PD-TR-Logic, integrates three layers of circuitry, which would improve camera responsiveness, reduce noise, and increase dynamic range. The leak comes from a source known as "Jukanlosreve," who claims the sensor is being developed specifically for Apple's 2026 iPhone lineup. Sony has long been Apple's sole image sensor supplier, so Samsung's entry would be a big shift in the iPhone's camera supply chain.

Variable Aperture

DSLR-Style

Apple intends to equip this year's iPhone 18 Pro models with a variable aperture lens, according to reports. Weibo-based leaker Digital Chat Station claims the main rear camera – what Apple calls the 48-megapixel Fusion camera – on both iPhone 18 Pro models will offer variable aperture, which would be a first for the iPhone. A variable-aperture system physically adjusts the lens opening, letting more light in for low-light shots or narrowing the opening for brighter scenes and deeper depth of field.

The main cameras on the iPhone 15 Pro, 16 Pro, and 17 Pro all use a fixed ƒ/1.78 aperture, where the lens is permanently set to its widest setting. With a variable lens, the iPhone 18 Pro would allow users to manually shift the aperture, similar to on a DSLR camera. This would mean more control over depth of field, enabling sharper focus on subjects or smoother background blur. Industry analyst Ming-Chi Kuo said in November 2024 that Apple's iPhone 18 Pro models will get the feature.

5G Satellite Internet

Non-Terrestrial Data

According to a report by The Information, Apple plans to add support for 5G networks that operate via satellites rather than Earth-based towers as early as next year. This advancement would allow future iPhones to gain full internet connectivity through satellite, not just limited emergency features.

If Apple meets the 2026 target, the first devices to feature 5G satellite internet would likely be the iPhone 18 Pro, iPhone 18 Pro Max, and the long-rumored foldable iPhone. Apple partners with Globalstar for its iPhone satellite features, but there is currently no service that delivers full 5G satellite internet directly to a smartphone, and the report did not specify who would supply it.

Simplified Camera Control

New Design

Apple is reportedly working to simplify the Camera Control button's design on iPhone 18 models in order to reduce costs. The current Camera Control button on iPhone 17 models uses both capacitive and pressure sensors beneath a sapphire crystal surface. The capacitive layer detects touch gestures, while the force sensor recognizes different pressure levels for taps, presses, and swipes.

However, according to the Weibo-based account Instant Digital, Apple will remove the capacitive sensing layer and retain only pressure sensing recognition in the second iteration to achieve all Camera Control functions on the iPhone 18. The simplified version is not about reducing functionality in the button, but about saving money. The current solution is said to be very expensive for Apple and is generating costly after-sales repairs.

New Colors

Three in Testing

Apple is rumored to be testing three new color options for the iPhone 18 Pro models: burgundy, brown, and purple. A burgundy finish would mark the first time the Pro and Pro Max models have been offered in any shade of red, apart from the lighter (PRODUCT)RED used on earlier devices. The iPhone 14 Pro and iPhone 14 Pro Max were previously available in Deep Purple, and Apple has never released an iPhone in a genuinely brown color.Related Roundup: iPhone 18Related Forum: iPhone
This article, "10 Reasons to Wait for This Year's iPhone 18 Pro" first appeared on MacRumors.com

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Cisco Patches ISE Security Vulnerability After Public PoC Exploit Release

Cisco has released updates to address a medium-severity security flaw in Identity Services Engine (ISE) and ISE Passive Identity Connector (ISE-PIC) with a public proof-of-concept (PoC) exploit. The vulnerability, tracked as CVE-2026-20029 (CVSS score: 4.9), resides in the licensing feature and could allow an authenticated, remote attacker with administrative privileges to gain access toView the full article
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Researchers Uncover NodeCordRAT Hidden in npm Bitcoin-Themed Packages

Cybersecurity researchers have discovered three malicious npm packages that are designed to deliver a previously undocumented malware called NodeCordRAT. The names of the packages, all of which were taken down as of November 2025, are listed below. They were uploaded by a user named "wenmoonx." bitcoin-main-lib (2,300 Downloads) bitcoin-lib-js (193 Downloads) bip40 (970 Downloads) "TheView the full article
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Master in Splunk Engineering: Comprehensive MLOps Pipeline Guide

Introduction: Problem, Context & Outcome
Modern enterprises generate vast volumes of machine data every second from applications, infrastructure, and cloud services. Engineers often struggle to monitor, correlate, and analyze this data effectively. Without proper observability, organizations face delayed incident detection, prolonged downtime, and security vulnerabilities.
The Master in Splunk Engineering program addresses these challenges by teaching professionals how to collect, analyze, and visualize machine data in real-time. Participants learn to design dashboards, set alerts, optimize searches, and ensure system reliability. This training empowers teams to proactively respond to issues, maintain compliance, and support enterprise decision-making.
Why this matters: Timely insights into operational data are critical for business continuity, performance, and security.
What Is Master in Splunk Engineering?
Master in Splunk Engineering is a professional course that equips learners with the skills to use Splunk for enterprise-scale monitoring, observability, and analytics. It covers data ingestion, indexing, searching, and visualization, turning raw logs into actionable insights.
For developers and DevOps teams, Splunk integrates seamlessly into CI/CD pipelines, cloud environments, and microservices architectures. Participants gain hands-on experience with forwarders, dashboards, alerting, SPL queries, and security monitoring. Real-world exercises, such as troubleshooting outages or detecting anomalies, provide practical, applicable skills.
Why this matters: Proficiency in Splunk ensures engineers can manage complex systems efficiently and improve operational outcomes.
Why Master in Splunk Engineering Is Important in Modern DevOps & Software Delivery
Splunk has become a cornerstone of observability and operational intelligence in modern enterprises. Traditional monitoring tools often fail to handle high-volume, high-velocity data, leaving teams blind to critical issues.
This course teaches professionals to correlate logs, metrics, and events for rapid issue detection. It strengthens CI/CD workflows by providing real-time system visibility, integrates with cloud platforms, and supports agile development. Additionally, Splunk plays a crucial role in security operations, helping teams detect threats and meet compliance requirements.
Why this matters: Comprehensive observability is essential for proactive system management, reliability, and business agility.
Core Concepts & Key Components
Data Collection and Forwarders
Purpose: Collect data from multiple sources efficiently.
How it works: Universal and heavy forwarders transmit logs to Splunk indexers securely.
Where it is used: Servers, cloud apps, containers, and security devices.
Indexing and Storage
Purpose: Organize and store data for fast retrieval.
How it works: Splunk indexes incoming data to enable rapid searches and correlation.
Where it is used: Enterprise observability, audit logging, and compliance reporting.
Search Processing Language (SPL)
Purpose: Perform precise data queries and analyses.
How it works: SPL allows filtering, aggregating, and visualizing data efficiently.
Where it is used: Log analysis, performance monitoring, and incident investigation.
Dashboards & Visualizations
Purpose: Provide actionable insights through visual representation.
How it works: Custom dashboards display metrics and trends derived from SPL queries.
Where it is used: Operational monitoring, executive reporting, and decision-making.
Alerts & Proactive Monitoring
Purpose: Notify teams of anomalies or threshold breaches.
How it works: Configured alerts trigger notifications based on conditions or patterns.
Where it is used: Incident management, security monitoring, and uptime assurance.
Security Monitoring & Compliance
Purpose: Detect threats and maintain regulatory compliance.
How it works: Correlates logs across endpoints and apps to flag abnormal behavior.
Where it is used: Security operations centers (SOC), threat intelligence, and audits.
Why this matters: Understanding these components equips engineers to implement scalable and effective observability solutions.
How Master in Splunk Engineering Works (Step-by-Step Workflow)
Identify Data Sources: Collect logs from applications, servers, cloud platforms, and network devices. Set Up Forwarders: Use Universal or Heavy Forwarders to transmit data to indexers. Index Data: Store and organize data for fast searching and analysis. Query Data with SPL: Extract patterns, detect anomalies, and filter logs. Create Dashboards: Visualize trends, system health, and alerts. Configure Alerts: Define thresholds and monitoring conditions for proactive notifications. Analyze & Optimize: Review historical data, generate insights, and refine monitoring strategies. Why this matters: Following a structured workflow ensures reliable, scalable observability and rapid incident response.
Real-World Use Cases & Scenarios
Application Monitoring: DevOps teams monitor deployments, detect errors, and rollback if needed. System Reliability: SREs track uptime, latency, and performance across distributed systems. Security Analytics: SOC teams identify threats, detect anomalies, and ensure compliance. Cloud Resource Monitoring: Cloud engineers track usage and optimize costs across AWS, Azure, and GCP. Business Insights: Analysts derive actionable intelligence from customer activity and transaction logs. Roles involved: DevOps Engineers, Developers, QA, SRE, Cloud Architects, and Security Analysts.
Why this matters: Demonstrates Splunk’s direct impact on operational efficiency, security, and business decision-making.
Benefits of Using Master in Splunk Engineering
Productivity: Streamline log analysis and troubleshooting. Reliability: Detect issues before they escalate. Scalability: Manage large, distributed data environments. Collaboration: Share dashboards and reports across teams. Why this matters: Enhances system performance, reduces downtime, and improves team efficiency.
Challenges, Risks & Common Mistakes
Common challenges include inefficient data onboarding, poorly written SPL queries, and alert fatigue. Beginners may collect excessive irrelevant logs, causing storage strain. Misconfigured dashboards can delay incident response or trigger false positives.
Mitigation involves defining clear objectives, optimizing indexing, tuning queries, and reviewing dashboards and alerts regularly.
Why this matters: Avoiding these pitfalls ensures Splunk delivers maximum operational value.
Comparison Table
FeatureTraditional LoggingSplunk EngineeringData VolumeLimitedEnterprise-scaleSearch SpeedSlowReal-timeData CorrelationManualAutomatedVisualizationBasicInteractive & AdvancedAlertingReactiveProactiveCloud IntegrationLimitedNative SupportSecurity MonitoringMinimalComprehensiveDevOps IntegrationWeakStrongScalabilityLowHighBusiness InsightsLimitedData-driven Why this matters: Highlights why Splunk is the preferred enterprise observability solution.
Best Practices & Expert Recommendations
Define objectives before onboarding data sources. Standardize naming conventions and indexing practices. Optimize SPL queries for efficient searches. Tailor dashboards to roles and responsibilities. Review and fine-tune alerts regularly. Integrate Splunk with CI/CD and cloud monitoring tools. Why this matters: Best practices ensure secure, scalable, and efficient Splunk deployments.
Who Should Learn or Use Master in Splunk Engineering?
Ideal for DevOps Engineers, SREs, Developers, QA, Cloud Engineers, and Security Analysts. Suitable for beginners and professionals seeking advanced enterprise observability skills. Organizations implementing monitoring and security systems benefit directly.
Why this matters: Proper learner targeting maximizes skill adoption and operational ROI.
FAQs – People Also Ask
1. What is Master in Splunk Engineering?
A comprehensive course for using Splunk in enterprise observability and analytics.
Why this matters: Prepares engineers for operational and security excellence.
2. Is Splunk relevant for DevOps?
Yes, widely used for monitoring, troubleshooting, and incident response.
Why this matters: Enables real-time visibility for DevOps teams.
3. Can beginners take this course?
Yes, it covers fundamentals and advanced enterprise use cases.
Why this matters: Provides a full learning path from novice to expert.
4. How does Splunk compare to traditional logging?
Offers automated correlation, advanced analytics, and real-time monitoring.
Why this matters: Modern enterprises require scalable analytics beyond legacy tools.
5. Can Splunk help with security monitoring?
Yes, for SIEM, threat detection, and compliance reporting.
Why this matters: Protects enterprise assets and data.
6. Does Splunk support cloud platforms?
Yes, AWS, Azure, GCP, and hybrid systems.
Why this matters: Critical for modern cloud observability.
7. What skills will I gain?
SPL queries, dashboards, alerting, incident response, troubleshooting.
Why this matters: Directly enhances operational effectiveness.
8. Is Splunk scalable?
Yes, designed for enterprise-scale data.
Why this matters: Supports growing and distributed infrastructures.
9. Does this course improve incident response?
Yes, for proactive detection and root cause analysis.
Why this matters: Minimizes downtime and service disruption.
10. Is Splunk widely used?
Yes, by enterprises globally for monitoring, observability, and security analytics.
Why this matters: Confirms demand and real-world applicability.
Branding & Authority
Offered by DevOpsSchool, a global leader in enterprise-grade DevOps training. Mentored by Rajesh Kumar, with 20+ years of expertise in DevOps & DevSecOps, SRE, DataOps, AIOps & MLOps, Kubernetes & Cloud Platforms, and CI/CD Automation.
Why this matters: Trusted mentorship ensures learners acquire enterprise-ready, job-relevant skills.
Call to Action & Contact Information
Enroll in the Master in Splunk Engineering course today:

Email: [email protected]
Phone & WhatsApp (India): +91 7004215841
Phone & WhatsApp (USA): +1 (469) 756-6329

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Coolify Discloses 11 Critical Flaws Enabling Full Server Compromise on Self-Hosted Instances

Cybersecurity researchers have disclosed details of multiple critical-severity security flaws affecting Coolify, an open-source, self-hosting platform, that could result in authentication bypass and remote code execution. The list of vulnerabilities is as follows - CVE-2025-66209 (CVSS score: 10.0) - A command injection vulnerability in the database backup functionality allows any authenticatedView the full article
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Comprehensive SonarQube Guide for Jenkins GitLab Pipelines

Introduction: Problem, Context & Outcome
Modern software engineering teams work under constant pressure to deliver features faster while maintaining stability and security. As release cycles shorten, issues such as hidden bugs, inconsistent coding practices, unmanaged technical debt, and late-stage security vulnerabilities become common. Manual code reviews are time-consuming and cannot scale with CI/CD-driven development models, leading to fragile deployments and operational failures.
SonarQube Engineer Training equips professionals with the skills required to automate code quality inspection across the software delivery lifecycle. The program focuses on integrating quality checks into DevOps pipelines, enabling early detection of issues and enforcing consistent standards. Learners gain practical knowledge to improve reliability, maintainability, and security in enterprise-grade systems.
Why this matters: Automated quality checks reduce production risks and support sustainable software delivery.
What Is SonarQube Engineer Training?
SonarQube Engineer Training is a specialized learning program focused on using SonarQube for continuous code quality management. It covers static code analysis, identification of bugs and code smells, detection of security vulnerabilities, and measurement of technical debt across multiple languages.
From a DevOps and software delivery standpoint, the training explains how SonarQube fits into real-world workflows. Developers, DevOps engineers, and QA teams learn how to apply automated quality rules, analyze reports, and maintain consistent standards throughout the development lifecycle.
Why this matters: Mastering SonarQube enables scalable and repeatable quality governance in modern software projects.
Why SonarQube Engineer Training Is Important in Modern DevOps & Software Delivery
DevOps practices emphasize automation, fast feedback, and continuous improvement. SonarQube supports these principles by providing continuous inspection of code during development and delivery. Many organizations use SonarQube to maintain quality while adopting Agile, cloud-native, and microservices architectures.
The training addresses common DevOps challenges such as uncontrolled technical debt, inconsistent review practices, and delayed vulnerability detection. By integrating SonarQube into CI/CD pipelines, teams ensure that only quality-approved code progresses through environments, reducing deployment failures and operational risk.
Why this matters: Quality gates in DevOps pipelines prevent defects from reaching production systems.
Core Concepts & Key Components
Static Code Analysis
Purpose: Identify defects and risks without executing applications.
How it works: SonarQube scans source code using defined rule sets.
Where it is used: Development environments and CI pipelines.
Quality Gates
Purpose: Enforce minimum quality standards.
How it works: Builds fail when defined thresholds are violated.
Where it is used: Continuous integration and release pipelines.
Technical Debt Tracking
Purpose: Control long-term maintainability risks.
How it works: Issues are mapped to estimated remediation effort.
Where it is used: Enterprise applications and long-running systems.
Security Vulnerability Detection
Purpose: Identify security flaws early.
How it works: Applies security rules aligned with industry standards.
Where it is used: APIs, web platforms, and regulated environments.
Multi-Language Support
Purpose: Ensure quality across diverse technology stacks.
How it works: Supports multiple programming languages in one platform.
Where it is used: Polyglot development teams.
Dashboards & Reporting
Purpose: Provide visibility into code health.
How it works: Visual dashboards show metrics, trends, and alerts.
Where it is used: Team reviews, audits, and management reporting.
Why this matters: These components collectively create a complete, automated code quality ecosystem.
How SonarQube Engineer Training Works (Step-by-Step Workflow)
Training begins with installing and configuring SonarQube in a controlled environment. Learners then connect repositories and perform baseline scans to understand current code quality.
Next, SonarQube is integrated with CI/CD tools so that every code commit is automatically analyzed. Participants learn to configure rules, interpret results, enforce quality gates, and plan remediation activities. Continuous monitoring ensures long-term improvement.
Why this matters: A structured workflow ensures SonarQube becomes part of everyday DevOps practices.
Real-World Use Cases & Scenarios
In enterprise DevOps teams, SonarQube validates code quality during every build. Developers receive early feedback, QA teams verify compliance, and DevOps engineers ensure quality enforcement in pipelines.
SRE and cloud teams rely on SonarQube to maintain reliability in distributed systems. Security teams use vulnerability reports to reduce exposure. Business leaders benefit from stable releases and predictable delivery timelines.
Why this matters: Practical use cases show how SonarQube improves both engineering and business outcomes.
Benefits of Using SonarQube Engineer Training
Productivity: Reduces rework through early issue detection Reliability: Prevents defective code from reaching production Scalability: Supports large teams and complex systems Collaboration: Aligns developers, QA, and DevOps teams Why this matters: These benefits directly impact delivery speed and software quality.
Challenges, Risks & Common Mistakes
Common challenges include ignoring SonarQube findings, misconfiguring quality gates, and failing to integrate analysis into CI/CD pipelines. Teams may also depend solely on default rules without customization.
These risks are mitigated through proper training, consistent enforcement, and regular review of quality reports.
Why this matters: Avoiding these mistakes ensures effective and sustainable adoption.
Comparison Table
AspectManual ReviewSonarQube-Based ReviewSpeedSlowAutomatedCoveragePartialFull codebaseConsistencyReviewer-dependentRule-basedSecurity DetectionLimitedBuilt-inReportingManualAutomated dashboardsScalabilityLowHighCI/CD IntegrationRareNativeTechnical Debt TrackingDifficultQuantifiedHuman ErrorHighLowEnterprise ReadinessLimitedStrong Why this matters: Automated analysis scales better than manual approaches.
Best Practices & Expert Recommendations
Integrate SonarQube early in development workflows. Customize quality rules based on project needs. Enforce quality gates consistently across teams. Review dashboards frequently and resolve issues incrementally. Ensure all contributors understand quality expectations.
Why this matters: Best practices ensure long-term value and enterprise readiness.
Who Should Learn or Use SonarQube Engineer Training?
This training is ideal for developers, DevOps engineers, QA professionals, SREs, and cloud engineers. Beginners gain foundational skills, while experienced professionals enhance automation and governance capabilities.
Why this matters: Broad adoption ensures organization-wide code quality improvement.
FAQs – People Also Ask
What is SonarQube Engineer Training?
It teaches automated code quality and security analysis.
Why this matters: Improves software reliability.
Why is SonarQube used in DevOps?
It integrates quality checks into pipelines.
Why this matters: Prevents faulty deployments.
Is SonarQube suitable for beginners?
Yes, it covers fundamentals first.
Why this matters: Easy entry point.
Does SonarQube support multiple languages?
Yes, it supports many popular languages.
Why this matters: Fits modern tech stacks.
Can SonarQube detect vulnerabilities?
Yes, it identifies security issues.
Why this matters: Improves application security.
Is SonarQube only for developers?
No, QA and DevOps teams use it too.
Why this matters: Encourages collaboration.
Does SonarQube reduce technical debt?
Yes, it tracks and measures debt.
Why this matters: Improves maintainability.
Can SonarQube block deployments?
Yes, via quality gates.
Why this matters: Protects production systems.
Is SonarQube enterprise-ready?
Yes, it is widely used at scale.
Why this matters: Proven reliability.
Does this training include CI/CD integration?
Yes, pipeline integration is included.
Why this matters: Real-world applicability.
Branding & Authority
DevOpsSchool is a globally trusted platform delivering enterprise-grade DevOps and software engineering education. The training is led by Rajesh Kumar, who brings over 20 years of hands-on expertise in DevOps & DevSecOps, Site Reliability Engineering (SRE), DataOps, AIOps & MLOps, Kubernetes & Cloud Platforms, and CI/CD Automation. The SonarQube Engineer Training prepares professionals to implement automated code quality governance at scale.
Why this matters: Expert-led instruction ensures industry-aligned, practical learning.
Call to Action & Contact Information
Email: [email protected]
Phone & WhatsApp (India): +91 7004215841
Phone & WhatsApp (USA): +1 (469) 756-6329

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Python for DevOps: Certification in Scripting Cloud Tools

Introduction: Problem, Context & Outcome
Python is one of the most widely used programming languages today, powering web applications, cloud automation, DevOps workflows, data engineering, and AI solutions. Despite its popularity, engineers often face challenges in applying Python effectively in real-world enterprise environments. Common obstacles include maintaining clean, reusable code, automating workflows, integrating with CI/CD pipelines, and managing cloud-native systems.
The Python Certification Training Course provides a comprehensive learning experience, combining foundational knowledge with advanced, hands-on Python applications. Participants learn scripting, automation, backend development, data handling, and testing, along with integration into DevOps pipelines. By the end of the program, learners can confidently implement Python in production-ready environments.
Why this matters: Acquiring Python skills enables professionals to improve operational efficiency, accelerate software delivery, and automate repetitive tasks in enterprise workflows.
What Is Python Certification Training Course?
The Python Certification Training Course is a structured program that teaches Python programming from beginner to advanced levels with a focus on enterprise applications. It covers core concepts like data types, control structures, functions, object-oriented programming, and libraries, along with advanced topics such as automation, testing, and cloud integration.
In DevOps and modern software delivery, Python is used to automate deployments, manage infrastructure, process data, and build backend services. Participants gain hands-on experience through real-world projects, ensuring they can apply Python effectively in production environments.
Why this matters: Learning Python in a structured, practical environment prepares professionals for real-world applications and enhances their career potential.
Why Python Certification Training Course Is Important in Modern DevOps & Software Delivery
Python is integral to modern DevOps workflows because of its simplicity, flexibility, and extensive ecosystem. It enables developers and engineers to automate CI/CD pipelines, monitor cloud environments, and build scalable applications efficiently. Python scripts can manage deployments, handle system monitoring, and interact with APIs seamlessly.
Organizations that adopt Python benefit from faster development cycles, improved reliability, and easier integration across software delivery pipelines. Its versatility makes it suitable for backend development, testing automation, and data processing in enterprise-grade systems.
Why this matters: Mastering Python ensures faster, more reliable, and automated software delivery, aligning with modern DevOps and cloud practices.
Core Concepts & Key Components
Python Basics
Purpose: Build a strong programming foundation.
How it works: Covers variables, data types, loops, functions, and basic modules.
Where it is used: General programming, automation, and scripting tasks.
Object-Oriented Programming (OOP)
Purpose: Organize code for scalability and maintainability.
How it works: Introduces classes, objects, inheritance, encapsulation, and abstraction.
Where it is used: Large-scale applications, backend systems, and enterprise software.
Python Libraries and Frameworks
Purpose: Use prebuilt tools to accelerate development.
How it works: Introduces libraries like NumPy, Pandas, Flask, Django, and Requests.
Where it is used: Web development, data analysis, API integration, and automation.
Scripting and Automation
Purpose: Reduce manual effort and improve efficiency.
How it works: Writing scripts to automate tasks, deployments, and system monitoring.
Where it is used: DevOps pipelines, cloud resource management, and operational automation.
Data Handling & Analysis
Purpose: Process, analyze, and visualize data efficiently.
How it works: Python reads, transforms, and processes structured and unstructured datasets.
Where it is used: Data-driven decision-making, analytics, reporting, and ETL processes.
Testing and Debugging
Purpose: Ensure reliability and maintainability of code.
How it works: Implements unit testing, integration testing, and debugging techniques.
Where it is used: Development pipelines, QA automation, and production systems.
Why this matters: Mastery of these concepts allows professionals to develop robust, maintainable, and production-ready Python applications.
How Python Certification Training Course Works (Step-by-Step Workflow)
The course begins with Python fundamentals, including syntax, data types, loops, functions, and modules. Learners then advance to object-oriented programming, modular code practices, and reusable design patterns.
Hands-on projects teach automation, scripting, CI/CD integration, cloud resource management, and backend development. Testing and debugging practices are incorporated to ensure production-ready code. This step-by-step workflow allows learners to gradually apply theory to practical enterprise scenarios.
Why this matters: A structured approach ensures learners gain comprehensive knowledge and real-world application skills for Python.
Real-World Use Cases & Scenarios
DevOps Automation: Automate CI/CD pipelines, deployments, and monitoring tasks using Python scripts. Web Development: Build REST APIs and backend services with Flask or Django frameworks. Data Engineering: Manage ETL processes, log analysis, and large dataset processing. QA Automation: Develop Python scripts for automated testing and application validation. Teams involve developers, DevOps engineers, QA professionals, and cloud architects, collaborating to implement Python solutions that improve efficiency and reduce operational risks.
Why this matters: Real-world examples highlight Python’s versatility and its impact across multiple enterprise functions.
Benefits of Using Python Certification Training Course
Productivity: Automates repetitive tasks and workflows. Reliability: Supports testing frameworks and reduces code errors. Scalability: Enables cloud-native, distributed applications. Collaboration: Improves code readability and maintainability across teams. Why this matters: Python enhances operational efficiency, supports automation, and ensures scalable, enterprise-ready solutions.
Challenges, Risks & Common Mistakes
Common challenges include writing disorganized code, over-reliance on third-party libraries without understanding them, skipping testing, and poor error handling. Beginners may also apply Python incorrectly in unsuitable scenarios.
Mitigation strategies include adhering to coding standards, implementing testing and debugging practices, and integrating Python into CI/CD pipelines and cloud workflows.
Why this matters: Awareness of common mistakes ensures safe, effective application of Python in enterprise projects.
Comparison Table
AspectTraditional ProgrammingPython ProgrammingSyntax ComplexityHighSimple and readableLearning CurveSteepBeginner-friendlyLibrariesLimitedExtensive and versatileAutomationManualScripted and automatedTestingManualIntegrated frameworksCloud IntegrationDifficultSupported nativelyData HandlingManualEfficient libraries like PandasWeb DevelopmentSeparate frameworksFlask/Django integrationDeploymentManual scriptsCI/CD automationScalabilityLimitedCloud-native ready Why this matters: Python improves productivity, reliability, and enterprise software delivery compared to traditional methods.
Best Practices & Expert Recommendations
Write modular, clean, and maintainable code. Use version control (Git) for all projects. Automate tasks with Python and integrate scripts into CI/CD pipelines. Leverage libraries while understanding their implementation. Test and debug code consistently to ensure reliability. Why this matters: Following best practices ensures Python applications are maintainable, scalable, and enterprise-ready.
Who Should Learn or Use Python Certification Training Course?
This course is ideal for developers, DevOps engineers, cloud architects, QA professionals, and data engineers. Both beginners and experienced professionals can benefit from learning Python for automation, application development, and enterprise integration.
Learners will gain skills to develop scalable applications, automate workflows, and implement Python in real-world projects.
Why this matters: Python expertise enhances career growth, operational efficiency, and cross-team collaboration.
FAQs – People Also Ask
What is Python Certification Training Course?
A structured program teaching Python from fundamentals to advanced enterprise applications.
Why this matters: Prepares learners to apply Python effectively in real-world scenarios.
Why should I learn Python?
Python is versatile, beginner-friendly, and widely used in automation, web development, and analytics.
Why this matters: Skills in Python increase career opportunities across industries.
Is it suitable for beginners?
Yes, the course starts from basics and progresses to advanced topics with hands-on exercises.
Why this matters: Accessible for learners of all levels.
How does Python compare to other languages?
Python is simpler, readable, and has a robust library ecosystem.
Why this matters: Reduces development time and improves maintainability.
Is Python relevant for DevOps roles?
Yes, it is widely used for automation, monitoring, and cloud management.
Why this matters: Enhances operational efficiency in DevOps workflows.
What libraries and frameworks are included?
NumPy, Pandas, Flask, Django, Requests, and testing frameworks.
Why this matters: Provides practical, industry-standard Python skills.
Does the course include automation?
Yes, including scripting, cloud automation, and CI/CD integration.
Why this matters: Reduces manual effort and improves workflow efficiency.
Can Python be used in cloud environments?
Yes, it integrates with AWS, Azure, and Google Cloud services.
Why this matters: Supports scalable cloud-native applications.
Does it cover testing and debugging?
Yes, unit testing, integration testing, and debugging are included.
Why this matters: Ensures reliable, production-ready code.
Can Python improve team collaboration?
Yes, Python’s readability improves code understanding across teams.
Why this matters: Enhances teamwork and maintainability of projects.
Branding & Authority
DevOpsSchool is a globally trusted platform for enterprise-grade learning. The program is led by Rajesh Kumar, with 20+ years of experience in DevOps & DevSecOps, Site Reliability Engineering (SRE), DataOps, AIOps & MLOps, Kubernetes & Cloud Platforms, and CI/CD Automation. This Python Certification Training Course ensures learners gain practical, industry-aligned skills.
Why this matters: Expert-led guidance provides actionable, enterprise-ready learning.
Call to Action & Contact Information
Email: [email protected]
Phone & WhatsApp (India): +91 7004215841
Phone & WhatsApp (USA): +1 (469) 756-6329

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Observability Engineering for SRE: Alerting Dashboards Best Practices

Introduction: Problem, Context & Outcome
Modern software systems are increasingly complex, running across microservices, containers, and cloud environments. Engineers often struggle to pinpoint performance issues, identify anomalies, and troubleshoot failures efficiently. Traditional monitoring solutions provide limited insights, leaving teams reactive instead of proactive, which can result in downtime, degraded user experience, and business impact.
The Master in Observability Engineering equips professionals with the expertise to implement comprehensive observability solutions. Through hands-on learning, participants gain skills in collecting metrics, analyzing logs, tracing requests across distributed systems, and setting up dashboards and alerts for proactive monitoring. This knowledge allows teams to identify and resolve problems before they affect users.
Why this matters: Observability ensures systems remain reliable, scalable, and performant, reducing downtime and improving operational efficiency.
What Is Master in Observability Engineering?
The Master in Observability Engineering is a professional training program designed to teach engineers how to monitor, trace, and analyze complex enterprise systems. It covers critical elements such as metrics collection, logging, distributed tracing, alerting, and visualization, emphasizing practical application in DevOps environments.
In real-world scenarios, observability goes beyond simple monitoring—it provides actionable insights into system behavior. Participants work with tools like Prometheus, Grafana, ELK Stack, and other cloud-native observability platforms. By the end of the program, learners can design and implement observability solutions to maintain system performance, reliability, and operational transparency.
Why this matters: Observability reduces troubleshooting time, enhances system reliability, and empowers teams to make data-driven decisions.
Why Master in Observability Engineering Is Important in Modern DevOps & Software Delivery
In today’s DevOps and cloud-native ecosystems, applications are distributed, dynamic, and continuously evolving. Observability enables teams to maintain end-to-end visibility into system performance, detect issues quickly, and prevent outages.
The program highlights integration of observability into CI/CD pipelines, allowing teams to monitor deployments, correlate metrics, logs, and traces, and respond proactively to anomalies. By embedding observability into the software delivery lifecycle, organizations improve performance, reduce downtime, and support Agile and DevOps workflows.
Why this matters: Observability is critical for delivering resilient, scalable, and high-performing applications in fast-paced enterprise environments.
Core Concepts & Key Components
Metrics Collection
Purpose: Measure system performance and health.
How it works: Collects CPU usage, memory consumption, response times, and error rates.
Where it is used: Application and infrastructure monitoring.
Logging
Purpose: Capture detailed system events.
How it works: Aggregates structured and unstructured logs for troubleshooting, auditing, and compliance.
Where it is used: Debugging, security monitoring, and operational analysis.
Tracing
Purpose: Track requests across distributed systems.
How it works: Assigns unique identifiers to requests to visualize latency and dependencies.
Where it is used: Microservice debugging, bottleneck detection, and root-cause analysis.
Alerting & Notification
Purpose: Notify teams about anomalies in real-time.
How it works: Configures thresholds and anomaly-based alerts sent via email, Slack, or other channels.
Where it is used: Incident management and proactive system maintenance.
Dashboards & Visualization
Purpose: Present system insights visually.
How it works: Combines metrics, logs, and traces into interactive dashboards for monitoring and reporting.
Where it is used: Team collaboration and executive reporting.
Observability Integration with CI/CD
Purpose: Embed monitoring into software deployment workflows.
How it works: Implements logging, metrics collection, and alerting into pipelines for continuous feedback.
Where it is used: Automated deployments and DevOps processes.
Why this matters: Mastering these components enables teams to maintain system visibility, detect issues early, and optimize performance efficiently.
How Master in Observability Engineering Works (Step-by-Step Workflow)
Observability begins by defining KPIs for critical systems. Engineers collect metrics, logs, and traces across services and infrastructure. Dashboards display performance and operational health, while alerting mechanisms notify teams of anomalies.
Data is analyzed to identify bottlenecks, errors, or latency. Observability is integrated into CI/CD pipelines, ensuring continuous feedback during deployments. Teams iterate on alerts, dashboards, and remediation processes to maintain high system availability and performance.
Why this matters: A structured workflow helps organizations detect and resolve issues rapidly, ensuring operational excellence.
Real-World Use Cases & Scenarios
Financial Services: Detecting fraudulent transactions and monitoring peak traffic uptime. E-commerce Platforms: Ensuring smooth checkout processes and system responsiveness. SaaS Applications: Monitoring performance, optimizing cloud resources, and reducing downtime. Roles involved include DevOps engineers, SREs, developers, QA teams, and cloud architects. Observability data informs deployment decisions, performance tuning, and incident response, directly impacting business outcomes and customer satisfaction.
Why this matters: Real-world examples illustrate how observability enhances operational efficiency and reduces risks.
Benefits of Using Master in Observability Engineering
Productivity: Accelerates detection and resolution of system issues. Reliability: Continuous monitoring ensures high uptime and performance. Scalability: Supports cloud-native, distributed architectures. Collaboration: Improves cross-team communication and shared insights. Why this matters: Implementing observability reduces operational overhead while maintaining system reliability.
Challenges, Risks & Common Mistakes
Common mistakes include monitoring irrelevant metrics, ignoring traces, alert fatigue, and lack of CI/CD integration. Beginners may misconfigure dashboards or overlook centralized logging. Risks include delayed incident response, undetected anomalies, and inefficient resource allocation.
Mitigation strategies involve defining meaningful KPIs, centralizing logs and metrics, automating alerts, and embedding observability into DevOps workflows.
Why this matters: Awareness of challenges ensures successful, scalable observability implementation.
Comparison Table
AspectTraditional MonitoringObservability EngineeringData CollectionMetrics onlyMetrics, logs, tracesAnalysisManualReal-time and automatedDeployment IntegrationRareIntegrated with CI/CDAlertingBasicAutomated, proactiveVisualizationStaticInteractive dashboardsTroubleshootingSlowRapid root-cause analysisScalabilityLimitedCloud-native readyCollaborationSiloedCross-functional insightsReliabilityReactiveProactive maintenanceBusiness ImpactLimitedActionable insights Why this matters: Observability provides deeper insights, faster troubleshooting, and improved operational efficiency.
Best Practices & Expert Recommendations
Define clear KPIs aligned with business goals. Centralize logs, metrics, and traces. Automate alerting to reduce manual effort. Integrate observability into CI/CD pipelines. Maintain dashboards and refine them based on incident learnings. Why this matters: Best practices ensure scalable, reliable, and maintainable observability systems.
Who Should Learn or Use Master in Observability Engineering?
This program is suitable for DevOps engineers, SREs, cloud architects, QA professionals, and developers. Beginners and experienced professionals benefit from learning observability frameworks, improving reliability, and integrating monitoring into CI/CD pipelines.
Learners gain practical skills to increase visibility, reduce downtime, and enhance cross-team collaboration.
Why this matters: Proper training ensures resilient, high-performing, and observable systems.
FAQs – People Also Ask
What is Master in Observability Engineering?
A professional program teaching monitoring, tracing, and system analysis.
Why this matters: Helps teams maintain reliable, transparent systems.
Why is observability important?
It provides actionable insights into system performance and behavior.
Why this matters: Allows proactive issue detection and resolution.
Is it suitable for beginners?
Yes, it covers foundational to advanced topics.
Why this matters: Accessible for all skill levels.
How does it differ from traditional monitoring?
It integrates metrics, logs, and traces for full system visibility.
Why this matters: Ensures faster detection and resolution of issues.
Is it relevant for DevOps roles?
Yes, observability integrates with CI/CD and cloud workflows.
Why this matters: Essential for modern DevOps and SRE teams.
Does it include cloud observability?
Yes, it covers tools and practices for cloud-native platforms.
Why this matters: Supports scalable, reliable enterprise systems.
Can it improve incident response?
Yes, it enables fast detection and resolution of problems.
Why this matters: Reduces downtime and operational risk.
What tools are included?
Prometheus, Grafana, ELK Stack, and cloud-native observability platforms.
Why this matters: Provides hands-on experience with industry-standard tools.
Does it include dashboards and visualization?
Yes, dashboards combine metrics, logs, and traces for operational insights.
Why this matters: Enhances team collaboration and visibility.
Can it benefit enterprise applications?
Yes, it improves reliability, performance, and operational insight.
Why this matters: Supports business continuity and end-user satisfaction.
Branding & Authority
DevOpsSchool is a globally trusted platform offering enterprise-grade training. Led by Rajesh Kumar, with 20+ years of expertise in DevOps & DevSecOps, SRE, DataOps, AIOps & MLOps, Kubernetes & Cloud, and CI/CD Automation, this Master in Observability Engineering ensures learners gain practical, production-ready skills.
Why this matters: Expert mentorship delivers actionable and industry-relevant learning.
Call to Action & Contact Information
Email: [email protected]
Phone & WhatsApp (India): +91 7004215841
Phone & WhatsApp (USA): +1 (469) 756-6329

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Top cyber threats to your AI systems and infrastructure

Attacks against AI systems and infrastructure are beginning to take shape in real-world instances, and security experts expect the number of these attack types will rise in coming years. In a rush to realize the benefits of AI, most organizations have played it fast and loose on security hardening when rolling out AI tools and use cases. As a result, experts also warn that many organizations aren’t prepared to detect, deflect, or respond to such attacks.
“Most are aware of the possibility of such attacks, but I don’t think a lot of people are fully aware of how to properly mitigate the risk,” says John Licato, associate professor in the Bellini College of Artificial Intelligence, Cybersecurity and Computing at the University of South Florida, founder and director of the Advancing Machine and Human Reasoning Lab, and owner of startup company Actualization.AI.
Top threats to AI systems
Multiple attack types against AI systems are arising. Some attacks, such as data poisoning, occur during training. Others, such as adversarial inputs, happen during inference. Still others, such as model theft, occur during deployment.
Here is a rundown of the top threat types to AI infrastructure experts warn about today. Some are more rare or theoretical than others, though many have been observed in the wild or have been demonstrated by researchers through notable proofs of concept.
Data poisoning
Data poisoning is a type of attack in which bad actorsmanipulate, tamper with, and pollute the data used to develop or train AI systems, including machine learning models. By corrupting the data or introducing faulty data, attackers can alter, bias, or otherwise render inaccurate a model’s performance.
Imagine an attack that tells a model that green means stop instead of go, says Robert T. Lee, CAIO and chief of research at SANS, a security training and certification firm. “It’s meant to degrade the output of the model,” he explains.
Model poisoning
Here, the attack goes after the model itself, seeking to produce inaccurate results by tampering with the model’s architecture or parameters. Some definitions of model poisoning models also include attacks where the model’s training data has been corrupted through data poisoning.
Tool poisoning
Invariant Labs identified this type of attack in spring 2025. When announcing its findings, Invariant wrote that it had “discovered a critical vulnerability in the Model Context Protocol (MCP) that allows for what we term Tool Poisoning Attacks. This vulnerability can lead to sensitive data exfiltration and unauthorized actions by AI models.”
The company went on to note that its experiments showed “that a malicious server can not only exfiltrate sensitive data from the user but also hijack the agent’s behavior and override instructions provided by other, trusted servers, leading to a complete compromise of the agent’s functionality, even with respect to trusted infrastructure.”
These attacks involve embedding malicious instructions inside MCP tool descriptions that, when interpreted by AI models, can hijack the model. These attacks essentially corrupt the MCP layer “to trick an agent to do something,” says Chirag Mehta, vice principal and principal analyst at Constellation Research.
For more on MCP threats, see “Top 10 MCP vulnerabilities: The hidden risks of AI integrations.”
Prompt injection
During a prompt injection attack, hackers use prompts that look legitimate but actually have embedded malicious commands meant to get the large language model to do something it shouldn’t. Hackers use these prompts to trick the model to bypass or override its guardrails, to share sensitive data, or to perform unauthorized actions.
“With prompt injection, you can change what the AI agent is supposed to do,” says Fabien Cros, chief data and AI officer at global consulting firm Ducker Carlisle.
Several notable prompt injection attacks and proofs of concept have been reported of late, including researchers tricking ChatGPT into prompt injecting itself, attackers embedding malicious prompts into document macros, and researchers demoing zero-click prompt attacks on popular AI agents.
Adversarial inputs
Model owners and operators use perturbed data to test models for resiliency, but hackers use it to disrupt. In an adversarial input attack, malicious actors feed deceptive data to a model with the goal of making the model output incorrect.
The changes to the perturbed input are typically small, or the deceptive data may be noise; the changes are deliberately designed to be subtle enough to evade detection by security systems but still capable of throwing off the model. This makes adversarial inputs a type of evasion attack.
Model theft/model extraction
Malicious actors can replicate, or reverse-engineer, a model, its parameters, and even its training data. They typically do this using publicly available APIs — for example, the model’s prediction API or a cloud services API — to repeatedly query the model and collect outputs.
They then can analyze how the model responds and use that analysis to reconstruct it.
“It’s enabling unauthorized duplication of the tools itself,” says Allison Wikoff, director and Americas lead for global threat intelligence at PwC.
Model inversion
Model inversion refers to a specific extraction attack in which the adversary attempts to reconstruct or infer the data that was used to train the model.
The name comes from the hackers “inverting” the model, using its outputs to reconstruct or reverse-engineer information about the inputs used to train the model.
Supply chain risks
Like other software systems, AI systems are built with a combination of components that can include open-source code, open-source models, third-party models, and various sources of data. Any security vulnerability in the components can show up in the AI systems. This makes AI systems vulnerable to supply chain attacks, where hackers can exploit vulnerabilities within the components to launch an attack.
For recent examples, see “AI supply chain threats loom — as security practices lag.”
Jailbreaking
Also called model jailbreaking, attackers’ goal here is to get AI systems — primarily through engaging with LLMs — to disregard the guardrails that confine their actions and behavior, such as safeguards to prevent harmful, offensive, or unethical outputs.
Hackers can use various techniques to execute this type of attack. For example, they could employ a role-playing exploit (aka role-play attack), using commands to instruct the AI to adopt a persona (such as a developer) that can work around the guardrails. They could disguise malicious instructions in seemingly legitimate prompts or use encoding, foreign words, or keyboard characters to bypass filters. They could also use a prompt framed as a hypothetical or research question or a series of prompts that leads to their end objective.
Those objectives, which also are varied, include getting AI systems to write malicious code, spread problematic content, and reveal sensitive data.
“When there is a chat interface, there are ways to interact with it to get it to operate outside the parameters,” Licato says. “That’s the tradeoff of having an increasingly powerful reasoning system.”
Counteracting threats to AI systems
While their executive colleagues jump into AI initiatives in search of enhanced productivity and innovation, CISOs must take an active role in ensuring security for those initiatives — and the organization’s AI infrastructure at large — is a top priority.
According to a recent survey from security tech company HackerOne, 84% of CISOs are now responsible for AI security and 82% now oversee data privacy. If CISOs don’t advance their security strategies to counteract attacks against AI systems and the data the feeds them, future issues will reflect on their leadership — regardless of whether they were invited to the table when AI initiatives were conceived and launched.
As a result, CISOs have a “need for a proactive AI security strategy,” according to Constellation’s Mehta.
“AI security is not just a technical challenge but also a strategic imperative requiring executive buy in and cross-functional collaboration,” he writes in his 2025 report AI Security Beyond Traditional Cyberdefenses: Rethinking Cybersecurity for the Age of AI and Autonomy. “Data governance is foundational, because securing AI begins with ensuring the integrity and provenance of training data and model inputs. Security teams must develop new expertise to handle AI-driven risks, and business leaders must recognize the implications of autonomous AI systems and the governance frameworks needed to manage them responsibly.”
Strategies for assessing, managing, and counteracting the threat of attacks on AI systems are emerging. In addition to maintaining strong data governance and other fundamental cyber defense best practices, AI and security experts say CISOs and their organizations should be evaluating AI models before deploying them, monitoring AI systems in use, and using red teams to test models.
CISOs may need to implement specific actions to counter certain attacks, says PwC’s Wikoff. For example, CISOs looking to head off model theft can monitor for suspicious queries and patterns as well as have timeouts and capture rate-limited responses. Or, to help prevent evasion attacks, security leaders could employ adversarial training — essentially training models to guard against those types of attacks.
Adopting MITRE ATLAS is another step. This framework, short for Adversarial Threat Landscape for Artificial-Intelligence Systems, provides a knowledge base mapping how attackers target AI systems and details identifying tactics, techniques, and procedures (TTPs).
Security and AI experts acknowledge the challenges of taking such steps. Many CISOs are contending with more immediate threats, including shadow AI and attacks that are getting faster, more sophisticated, and harder to detect, thanks in part to attackers’ use of AI. And given that attacks on AI systems are still nascent, with some attack types still considered theoretical, CISOs face challenges in getting resources to develop strategies and skills to counteract attacks on AI systems.
“For the CISO this is something that’s really difficult, because attacks on AI backends is still being researched. We’re at the early stages of figuring out what hackers are doing and why,” Lee, of SANS, says.
Lee and others recognize the competitive pressure on organizations to make the most of AI, yet they stress that CISOs and their executive colleagues can’t let securing AI systems be an afterthought.
“Thinking about what these attacks could be as they build the infrastructure is key for the CISO,” says Matt Gorham, leader of PwC’s Cyber and Risk Innovation Institute.
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CSOonline

OpenAI Launches ChatGPT Health with Isolated, Encrypted Health Data Controls

Artificial intelligence (AI) company OpenAI on Wednesday announced the launch of ChatGPT Health, a dedicated space that allows users to have conversations with the chatbot about their health. To that end, the sandboxed experience offers users the optional ability to securely connect medical records and wellness apps, including Apple Health, Function, MyFitnessPal, Weight Watchers, AllTrails,View the full article
Hacker News

From Basics to Pro: Machine Learning DevOps Certification

Introduction: Problem, Context & Outcome
In today’s data-driven world, organizations are producing massive volumes of information daily. However, turning this data into actionable insights is a significant challenge. Engineers and data teams often struggle to develop accurate predictive models, deploy them efficiently, and integrate ML workflows into DevOps pipelines. Without proper training, this can lead to unreliable models, delayed deployments, and ineffective decision-making.
The Master in Machine Learning Course equips professionals with the skills to design, implement, and operationalize machine learning systems in enterprise environments. Participants learn to build production-ready pipelines, integrate models with cloud platforms, and monitor performance effectively.
Why this matters: Developing ML expertise allows organizations to transform raw data into actionable business value reliably and efficiently.
What Is Master in Machine Learning Course?
The Master in Machine Learning Course is an advanced professional program designed to teach the end-to-end lifecycle of ML systems. It covers supervised, unsupervised, and reinforcement learning, along with real-world datasets, feature engineering, model evaluation, and deployment practices.
In a modern DevOps context, ML models must integrate with CI/CD pipelines, automated monitoring, and cloud infrastructure. This course bridges the gap between theory and production, helping learners create models that are scalable, maintainable, and enterprise-ready.
Why this matters: Combining ML with operational practices ensures solutions are robust, scalable, and reliable.
Why Master in Machine Learning Course Is Important in Modern DevOps & Software Delivery
Machine learning is increasingly central to modern software systems, enabling AI-driven decision-making across industries like finance, healthcare, and e-commerce. However, productionizing ML models presents challenges, including deployment complexity, monitoring, and integration with agile DevOps workflows.
The Master in Machine Learning Course emphasizes production-ready practices, teaching learners to integrate models into CI/CD pipelines, deploy on cloud and containerized environments, and monitor their performance continuously. Adopting these practices accelerates innovation, reduces operational risks, and improves model reliability.
Why this matters: Enterprise ML succeeds only when models are production-ready and aligned with DevOps best practices.
Core Concepts & Key Components
Supervised Learning
Purpose: Predict outcomes using labeled data.
How it works: Models learn patterns from historical data to forecast future events.
Where it is used: Credit scoring, sales forecasting, customer churn prediction.
Unsupervised Learning
Purpose: Identify hidden patterns without labeled data.
How it works: Algorithms detect structures in the data using clustering or dimensionality reduction.
Where it is used: Customer segmentation, anomaly detection, recommendation systems.
Reinforcement Learning
Purpose: Optimize decision-making over time.
How it works: Agents learn from feedback and rewards to improve strategies.
Where it is used: Robotics, recommendation engines, automated trading.
Data Preprocessing & Feature Engineering
Purpose: Improve model performance and accuracy.
How it works: Cleans, transforms, and selects relevant features from raw data.
Where it is used: Preparing datasets for training and testing ML models.
Model Evaluation & Validation
Purpose: Ensure models generalize well to new data.
How it works: Metrics like accuracy, precision, recall, and F1-score are used.
Where it is used: Before deploying models into production environments.
Deployment & Monitoring
Purpose: Operationalize ML models effectively.
How it works: Integrates models with cloud services, APIs, and monitoring dashboards.
Where it is used: Real-time analytics, predictive decision systems, and AI-driven applications.
Why this matters: Understanding these components ensures ML models are reliable, scalable, and production-ready.
How Master in Machine Learning Course Works (Step-by-Step Workflow)
The process begins with problem definition and dataset collection. Data is preprocessed and features engineered to prepare it for model training. Algorithms—supervised, unsupervised, or reinforcement learning—are applied depending on the business goal.
Next, models are validated using real-world metrics to ensure performance. Deployment integrates models into CI/CD pipelines using cloud infrastructure and containerization. Continuous monitoring and retraining maintain model accuracy over time.
Why this matters: A structured workflow reduces errors, improves scalability, and ensures reliable ML deployments.
Real-World Use Cases & Scenarios
Financial institutions use ML for fraud detection and credit risk assessment, enhancing accuracy and compliance. E-commerce platforms leverage ML for personalized recommendations, dynamic pricing, and inventory optimization. Healthcare organizations use predictive models for patient outcome forecasting and operational planning.
Teams comprising data scientists, DevOps engineers, QA analysts, and cloud architects collaborate to deliver production-ready ML solutions. Operational ML pipelines accelerate insights, enhance customer experience, and generate measurable business value.
Why this matters: Real-world ML applications show how enterprise AI can improve decision-making and operational efficiency.
Benefits of Using Master in Machine Learning Course
Productivity: Accelerates development and deployment of ML models Reliability: Ensures models are validated, monitored, and production-ready Scalability: Supports large datasets and distributed pipelines Collaboration: Aligns data teams, DevOps, and business units Why this matters: These benefits enable organizations to leverage data as a strategic asset.
Challenges, Risks & Common Mistakes
Typical mistakes include using inappropriate algorithms, poor-quality datasets, overfitting models, and ignoring deployment or monitoring considerations. Beginners often overlook model versioning and retraining. Operational risks include inefficient pipelines and suboptimal cloud usage.
Mitigation strategies include strong data governance, CI/CD integration, automated testing, and continuous monitoring.
Why this matters: Awareness of risks ensures stable, scalable, and maintainable ML deployments.
Comparison Table
AspectTraditional AnalyticsMaster in Machine Learning CourseData ProcessingManualAutomated pipelinesModel AccuracyLowHigh with feature engineeringScalabilityLimitedCloud-ready & distributedDeploymentManualCI/CD integratedCollaborationSiloedCross-functional alignmentMonitoringMinimalReal-time performance trackingDecision SupportBasic reportsPredictive & prescriptive insightsReusabilityLowModular & reusable modelsAdaptabilitySlowContinuous learning pipelinesEnterprise IntegrationWeakCloud and API-ready Why this matters: Structured ML workflows outperform traditional analytics in enterprise settings.
Best Practices & Expert Recommendations
Maintain high-quality datasets and follow strict data governance. Choose algorithms aligned with business objectives. Implement CI/CD pipelines, automated testing, and continuous monitoring.
Use modular workflows for preprocessing, modeling, validation, and deployment. Collaborate with DevOps, QA, and cloud teams to reduce operational risks.
Why this matters: Following best practices ensures consistent, reliable, and scalable ML systems.
Who Should Learn or Use Master in Machine Learning Course?
This course is ideal for data scientists, developers, DevOps engineers, QA analysts, cloud architects, and SRE professionals. Beginners with programming knowledge and intermediate professionals seeking production-grade ML skills will benefit most.
Participants gain skills to deploy models in cloud and CI/CD environments and collaborate across teams effectively.
Why this matters: Proper learner targeting ensures maximum practical impact and skill retention.
FAQs – People Also Ask
What is Master in Machine Learning Course?
A professional program to learn building, deploying, and managing production-ready ML models.
Why this matters: Provides foundational skills for enterprise AI implementation.
Is it suitable for DevOps roles?
Yes, it covers CI/CD, monitoring, and cloud deployment.
Why this matters: Aligns ML with enterprise DevOps practices.
Can beginners take this course?
Yes, with programming and basic data knowledge.
Why this matters: Makes advanced ML accessible and practical.
Does it cover cloud deployment?
Yes, includes cloud and Kubernetes-ready models.
Why this matters: Cloud readiness is essential for production ML systems.
Is it hands-on?
Yes, includes exercises and real-world datasets.
Why this matters: Practical experience reinforces learning outcomes.
What skills are required?
Programming, statistics, and data handling basics.
Why this matters: Ensures participants can effectively follow course content.
Does it cover MLOps & AIOps?
Yes, end-to-end ML lifecycle management is included.
Why this matters: Prepares learners for operational ML challenges.
Is it better than traditional analytics training?
Yes, emphasizes predictive modeling and production deployment.
Why this matters: Delivers more business value than standard analytics programs.
Can it improve career growth?
Yes, prepares professionals for ML, DevOps, and data-driven roles.
Why this matters: Equips learners with in-demand enterprise skills.
Does it include real datasets for practice?
Yes, multiple datasets are provided for hands-on exercises.
Why this matters: Enhances practical learning and industry readiness.
Branding & Authority
DevOpsSchool is a globally trusted platform offering enterprise-aligned training programs. The program is led by Rajesh Kumar, with over 20 years of hands-on expertise in DevOps & DevSecOps, Site Reliability Engineering (SRE), DataOps, AIOps & MLOps, Kubernetes & Cloud Platforms, and CI/CD & Automation.
Why this matters: Expert mentorship ensures learners acquire practical, industry-ready skills.
Call to Action & Contact Information
Start your journey with Master in Machine Learning Course today.
Email: [email protected]
Phone & WhatsApp (India): +91 7004215841
Phone & WhatsApp (USA): +1 (469) 756-6329

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Beginner to Pro: TypeScript NestJS SRE Certification Path

Introduction: Problem, Context & Outcome
In today’s fast-paced software landscape, engineering teams often struggle to build backend systems that scale effectively and remain reliable across environments. JavaScript’s dynamic nature can lead to runtime errors, unpredictable APIs, and inconsistent coding practices as projects grow. In DevOps-driven organizations, these issues slow down CI/CD pipelines, complicate deployments, and introduce operational risks.
Master in TypeScript with NestJS provides a structured solution by combining the type safety of TypeScript with the modular, enterprise-ready NestJS framework. This approach empowers developers to create predictable, maintainable, and cloud-ready backend services aligned with modern DevOps practices. Engineers and DevOps teams can deliver faster, safer releases with improved reliability.
Why this matters: Strong backend architecture directly impacts deployment speed, operational stability, and business continuity.
What Is Master in TypeScript with NestJs?
Master in TypeScript with NestJS is a professional learning program and methodology for building scalable backend applications. TypeScript enhances JavaScript with static typing, reducing runtime errors and improving maintainability. NestJS provides a modular, opinionated framework that promotes clean architecture, dependency injection, and consistent design patterns.
In real-world applications, this combination is used to develop REST APIs, microservices, and event-driven backend systems. It integrates seamlessly with containerized deployments, CI/CD pipelines, and cloud platforms. Teams adopt this methodology to minimize bugs, ensure consistent architecture, and facilitate collaboration between development, QA, and operations.
Why this matters: Structured backend development reduces technical debt and ensures long-term maintainability.
Why Master in TypeScript with NestJs Is Important in Modern DevOps & Software Delivery
Modern DevOps practices prioritize automation, reliability, and rapid delivery. Backend systems need to be scalable, predictable, and resilient to frequent changes. Master in TypeScript with NestJs supports these goals by providing strong typing, modular design, and architectural clarity from the outset.
Organizations adopting this approach benefit from better CI/CD integration, cloud readiness, and microservices-friendly designs. NestJS supports API gateways, messaging patterns, and service orchestration, while TypeScript catches errors before production. Agile and DevOps teams gain faster feedback loops, safer releases, and improved collaboration across development and operations.
Why this matters: DevOps effectiveness depends on backend systems designed for automation, stability, and rapid iteration.
Core Concepts & Key Components
TypeScript Type System
Purpose: Prevent runtime errors and improve code clarity.
How it works: Introduces static typing, interfaces, and compile-time checks.
Where it is used: Data models, API contracts, business logic, and integrations.
NestJS Modular Architecture
Purpose: Promote organized, maintainable code.
How it works: Uses modules, controllers, and providers with dependency injection.
Where it is used: Enterprise APIs, microservices, and large backend platforms.
Dependency Injection
Purpose: Enhance flexibility and testability.
How it works: Automatically manages object creation and lifecycle.
Where it is used: Services, repositories, and external integrations.
Controllers & Routing
Purpose: Map incoming requests cleanly to services.
How it works: Defines HTTP routes handled by controller methods.
Where it is used: REST APIs, microservices, and backend gateways.
Middleware & Interceptors
Purpose: Handle cross-cutting concerns such as logging and authentication.
How it works: Executes logic before or after request processing.
Where it is used: Performance monitoring, logging, security, and caching.
Configuration & Environment Management
Purpose: Enable smooth deployment across environments.
How it works: Centralized configuration using environment variables.
Where it is used: Development, staging, production, and cloud deployments.
Why this matters: Mastery of these components ensures systems are scalable, maintainable, and production-ready.
How Master in TypeScript with NestJs Works (Step-by-Step Workflow)
The workflow starts by defining data models and interfaces using TypeScript to ensure consistency across all services. Applications are structured into NestJS modules organized by business functionality.
Controllers handle incoming requests, while services contain core business logic. Dependency injection reduces tight coupling and simplifies testing. Configuration management allows easy adaptation across environments.
In a DevOps context, applications are containerized, tested through CI pipelines, and deployed to cloud or Kubernetes platforms. Logging, monitoring, and health checks are built-in from the start.
Why this matters: A clear, repeatable workflow reduces operational risk and supports continuous delivery.
Real-World Use Cases & Scenarios
In financial technology, teams use this approach to build secure transaction systems with minimized runtime errors. E-commerce platforms rely on it for product management, order processing, and user services at scale.
SaaS companies deploy NestJS-based microservices for subscriptions, notifications, and third-party integrations. DevOps engineers gain deployment consistency, QA teams benefit from predictable APIs, and SRE teams improve observability and reliability.
Why this matters: Proven adoption demonstrates scalability across industries and team sizes.
Benefits of Using Master in TypeScript with NestJs
Productivity: Faster development with fewer bugs Reliability: Early error detection through static typing Scalability: Modular architecture supports growth Collaboration: Clear contracts enhance cross-team alignment Why this matters: These advantages accelerate delivery while improving system stability.
Challenges, Risks & Common Mistakes
Common issues include improper module design, misuse of TypeScript types, and skipping automated testing. Teams may overlook logging, monitoring, or configuration management.
Structured learning, adherence to best practices, and DevOps-aligned workflows help mitigate these risks.
Why this matters: Awareness of common pitfalls prevents costly production failures.
Comparison Table
AspectTraditional Node.jsMaster in TypeScript with NestJsTypingDynamicStatic typingArchitectureUnstructuredModular & opinionatedScalabilityManualBuilt-in supportTestingLimitedDependency-injection basedDevOps FitMediumHighCI/CD SafetyLowerHigherError DetectionRuntimeCompile-timeCollaborationInconsistentStandardizedCloud ReadinessBasicCloud-nativeEnterprise AdoptionLimitedStrong Why this matters: Comparison highlights why structured backend frameworks are preferred for modern enterprise systems.
Best Practices & Expert Recommendations
Enable strict TypeScript checks. Organize modules by business functionality. Integrate automated testing early in CI/CD pipelines. Apply environment-specific configurations for deployments.
Include logging, metrics, and health checks from day one. Refactor regularly to maintain clarity and prevent technical debt.
Why this matters: Following best practices ensures maintainable, enterprise-ready backends.
Who Should Learn or Use Master in TypeScript with NestJs?
Backend developers building scalable APIs, DevOps engineers managing deployment pipelines, and QA/cloud/SRE professionals benefit from predictable and testable services.
Intermediate professionals and motivated beginners with JavaScript fundamentals will gain the most from structured learning.
Why this matters: Proper audience alignment ensures effective adoption and real-world applicability.
FAQs – People Also Ask
What is Master in TypeScript with NestJs?
A structured methodology for building scalable, type-safe backend systems.
Why this matters: Correct understanding ensures successful implementation.
Is it suitable for DevOps roles?
Yes, it integrates well with CI/CD and cloud infrastructure.
Why this matters: DevOps alignment reduces operational risk.
Is NestJS better than Express?
NestJS provides structured, maintainable architecture.
Why this matters: Structured code improves long-term maintainability.
Can beginners learn it?
Yes, with JavaScript knowledge and guidance.
Why this matters: Clear learning paths increase adoption success.
Does it support microservices?
Yes, with native microservice support.
Why this matters: Microservices are widely adopted in enterprises.
Is TypeScript mandatory?
Yes, it ensures type safety and predictability.
Why this matters: Type safety reduces runtime failures.
Does it work with Kubernetes?
Yes, it is cloud-native and container-ready.
Why this matters: Kubernetes is standard in modern deployments.
Is it good for APIs?
Excellent for REST and event-driven APIs.
Why this matters: APIs are the backbone of modern software.
Does it improve testing?
Yes, dependency injection simplifies automated testing.
Why this matters: Testing ensures reliability and faster releases.
Is it enterprise-ready?
Yes, widely adopted in production systems.
Why this matters: Enterprise readiness ensures scalability and stability.
Branding & Authority
DevOpsSchool is a globally recognized platform delivering enterprise-grade DevOps and cloud-native training. The program is led by Rajesh Kumar, an expert with over 20 years of hands-on experience in DevOps & DevSecOps, Site Reliability Engineering (SRE), DataOps, AIOps & MLOps, Kubernetes & Cloud Platforms, and CI/CD & Automation.
Why this matters: Expertise ensures industry-relevant, practical learning.
Call to Action & Contact Information
Start building enterprise-ready backend systems today with Master in TypeScript with NestJs.
Email: [email protected]
Phone & WhatsApp (India): +91 7004215841
Phone & WhatsApp (USA): +1 (469) 756-6329

View the full article
reporter

CISA Flags Microsoft Office and HPE OneView Bugs as Actively Exploited

The U.S. Cybersecurity and Infrastructure Security Agency (CISA) on Wednesday added two security flaws impacting Microsoft Office and Hewlett Packard Enterprise (HPE) OneView to its Known Exploited Vulnerabilities (KEV) catalog, citing evidence of active exploitation. The vulnerabilities are listed below - CVE-2009-0556 (CVSS score: 8.8) - A code injection vulnerability in Microsoft OfficeView the full article
Hacker News

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