Doin’ DevOps
Ten Great DevOps Job Opportunities
DevOps.com is now providing a weekly DevOps jobs report through which opportunities for DevOps professionals will be highlighted as part of an effort to better serve our audience ...
Why Most DevSecOps Pipelines Fail at Runtime Security (not Build Time)
Nazim Ghori | | configuration drift, Continuous integration (CI/CD), DevSecOps pipelines, Infrastructure as Code (IaC), runtime security, security automationRuntime risk refers to security exposure caused by configuration, identity or infrastructure changes after deployment ...
Five Great DevOps Job Opportunities
Mike Vizard | | Agentic AI Engineering, Capital Markets DevOps, Cloud Engineer Salaries, DevOps Jobs 2026, DevOps Manager Hiring, Remote DevOps Careers, Senior DevOps Engineer Roles, Tech Salary Trends 2026Explore this week’s top DevOps and Platform Engineering roles. From $300k Cloud Engineering in Maryland to cutting-edge Agentic AI positions at T-Mobile ...
Microsoft Field Engineers Built a Six-Agent Research Pipeline in VS Code That Fact-Checks Its Own Output
Tom Smith | | Agent Handoff Pattern, Azure Kubernetes Service (AKS), Azure Red Hat OpenShift (ARO), Fact-Checking AI, GitHub Copilot Agents, Global Black Belts (GBB), Grounding, MCP Server, multi-agent systems, Project Nighthawk, Technical Research Automation, VS Code Agent SkillsAzure Global Black Belts Diego Casati and Ray Kao developed Project Nighthawk, a multi-agent system that automates deep technical research for AKS and ARO with 100% source-grounding ...
How AI is Shaping Modern DevOps and DevSecOps
AI is reshaping DevOps and DevSecOps by improving CI/CD workflows, DORA metrics and security without adding unnecessary complexity ...
Meta Researchers Show AI Agents Can Verify Code Without Running It — and Hit 93% Accuracy
Tom Smith | | Agentic Code Reasoning, AI coding agents, Code Equivalence Verification, Defects4J Benchmark, DevOps Code Review, Execution-Free Reward Signals, Meta Research, Reinforcement Learning Training, RubberDuckBench, Semi-Formal Reasoning, software lifecycle engineering, static analysisMeta's semi-formal reasoning enables AI agents to verify code without executing it, achieving 93% accuracy. Implications for code review and RL training costs ...
Policy as Code for Cost Control, Not Just Compliance
Mariusz Michalowski | | cloud cost management, FinOps, infrastructure as code, kubernetes, platform engineering, policy as codePolicy as code can do more than enforce compliance. Learn how platform teams use guardrails, tagging and sizing policies to prevent cloud cost waste early ...
The Green Side of Observability: Why Less Data Can Mean More Insight
Observability can generate massive data volumes. Learn how sustainable observability reduces telemetry waste, lowers costs and improves insight ...
The Observability Bill is Coming Due – and AI Wrote Most of It
Alan Shimel | | agentic telemetry, AI in development, AIOps, APM (Application Performance Management), CI/CD (Continuous Integration/Continuous Deployment), data management, data quality, devops, instrumentation, Logging Standards, observability, Sawmills, Signal-to-Noise Ratio, software engineering, technology innovation, telemetry management, Telemetry OptimizationObservability has always had a data quality problem. AI coding agents just made it catastrophically worse. Shimmy sits down with the co-founders of Sawmills to dig into why unmanaged telemetry is the ...
Gemini Code Assist Gets Agent Auto-Approve, Inline Diffs, and Custom Commands to Speed Up the Core Coding Loop
Tom Smith | | Agent Mode, AI coding agents, AI-assisted development, Auto Approve, code review, Context Drawer, custom commands, developer productivity, devops, Finish Changes, Gemini Code Assist, Google Gemini, inline diff, IntelliJ, Outlines, software lifecycle, VS CodeGoogle’s latest Gemini Code Assist updates focus on workflow, not hype: Agent Mode with Auto Approve, inline diffs, a Context Drawer, custom commands, Finish Changes, and Outlines streamline how developers review, trust, ...
Microsoft Azure Skills Plugin Gives AI Coding Agents a Playbook for Cloud Deployment
Tom Smith | | agent orchestration, AI coding agents, AI in software delivery, Azure automation, Azure cost optimization, Azure Skills Plugin, Claude Code, cloud deployment, devops, Foundry MCP, GitHub Copilot, guardrails, infrastructure as code, institutional knowledge, MCP Server, Microsoft Azure, platform engineering, VS Code agent pluginsMicrosoft’s new Azure Skills Plugin closes the gap between AI-written code and production deployments by packaging expert Azure knowledge as executable skills, backed by MCP servers for real infrastructure actions and AI ...
How We Got Here: Alert Fatigue to Decision Fatigue
AI and observability reduced alert fatigue, but decision fatigue remains. Decision architecture helps DevOps teams scale operational judgment ...
