Overcoming IP Churn in Ephemeral DevOps Environments Using Userspace Overlays
Modern DevOps practices have completely transformed how we handle compute and orchestration. Tools like Kubernetes enable engineering teams to spin up ephemeral containers in seconds and scale workloads dynamically to meet global demand. Yet the underlying network infrastructure has remained stubbornly rigid. Traditional cloud networking relies heavily on static IP addresses, rigid firewall rules, and […]
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. Our goal in these challenging economic times is to make it just that much easier for DevOps professionals to advance their careers. Of course, the pool of […]
xAI Opens Grok Build 0.1 to Developers via API
xAI’s Grok Build 0.1 is now available in public beta via the xAI API — a fast, purpose-built coding model for agentic workflows, debugging, and MCP support.
Claude Code’s Dynamic Workflows Take on the Tasks That Were Too Big to Automate
Anthropic’s Claude Code dynamic workflows run parallel subagents to tackle codebase-wide audits, large migrations, and complex engineering tasks end-to-end.
Claude Code Security Catches Vulnerabilities While You Write Code
Claude Code Security uses AI reasoning to catch complex vulnerabilities in code — including logic flaws that traditional static analysis tools consistently miss.
Microsoft Brings MCP to Geospatial Workflows With Planetary Computer Pro Tools for VS Code
Microsoft’s Planetary Computer Pro MCP Tools for VS Code bring 35+ geospatial tools into GitHub Copilot via natural-language prompts.
The Validation Gap Is Costing You More Than You Think
Our latest State of Software Delivery report analyzed more than 28 million CI workflows and found a pattern that should give engineering leaders pause. Average throughput grew 59% year over year. Main branch activity for the median team declined 7%. Teams are generating more code than ever before. Less of it is reaching production. The […]
Why Enterprise AI Infrastructure Is Becoming a DevOps Problem
Most enterprise AI projects start with retrieval. You connect Jira, Confluence, SharePoint, and Slack. Maybe a few internal databases nobody has touched in five years. You tune embeddings, optimize chunking, wire up a vector database, and convince yourself you’ve built an AI-powered knowledge system. Then the model server crashes. And suddenly, you discover the uncomfortable […]
AI Is Changing How We Write Infrastructure, But It’s Not Solving How We Control It
Over the past year, AI has fundamentally changed how software is written. Infrastructure code is no exception. Tasks that once required deep familiarity with tools, syntax, and workflows can now be handled through natural language. Engineers are no longer starting from a blank file. In many cases, reviewing and modifying code generated for them has […]
Why Logs, Metrics and Traces Still Don’t Give You Real Observability
If your team can answer the question “Did the system do the right thing?” and not just “Did the system stay up?”, you’re getting close to real observability.
Why Your AI Agent is a Black Box and How to fix it With OpenTelemetry
You built the agent. It works in testing. Then it hits production and starts giving wrong answers, timing out or burning through your token budget, and you have no idea why. This is when developers discover that print statements and log files weren’t designed for this. LLM applications fail in ways that traditional tooling can’t see. A hallucination doesn’t throw […]
Agentic SRE: The Next Frontier of Reliability
Agentic SRE is the evolution of site reliability engineering where AI agents help observe systems, reason over telemetry and take bounded operational actions under human-defined guardrails.
Why AI Won’t Solve the Hardest Part of Integrations
AI is making it easier for SaaS companies to build integrations. Give a coding agent decent API docs, some context about the systems involved, and a clear prompt, and it can get surprisingly far. It can write the logic faster than most teams could a year or two ago, saving time, reducing repetitive work, and […]
Harness Adds Pair of Tools to Track ROI in AI Coding
Harness today added two tools to track and analyze the impact code generated by artificial intelligence (AI) coding tools is having on application development. An AI Development Lifecycle (DLC) tool installs agent software on a developer’s machine to track adoption, sessions, and the code created across every coding agent, while a Cloud & AI Cost […]
IBM, Red Hat Launch Project Lightwell to Secure Open Source Software from Frontier Models
IBM and Red Hat are bringing together what they’ve learned from frontier AI models and 20,000 engineers to launch Project Lightwell, a $5 billion initiative aimed at helping enterprises better secure their open source software, work that has become more challenging in the age of such models as Anthropic’s Claude Mythos Preview. Mythos and similarly […]
More Signal, Less Clarity: The Observability Paradox No One Wants to Talk About
Record observability spending is driving up MTTR. Discover why tool sprawl and excessive dashboard data cause cognitive overload for on-call engineers, and how to fix it.
Why Agent Skills Are the Next Evolution of Software Development
The emergence of agent skills — modular, reusable blocks of natural language instructions and metadata — is transforming the developer’s role.
The Future of Salesforce DevOps: Preparing for the AI Era
By establishing a robust DevOps foundation now, organizations can leverage these emerging predictive capabilities to transform reactive pipelines into proactive, self-correcting release architectures.
The End of Alert Fatigue: How AI-Powered Observability is Transforming SRE Teams in 2026
Alert fatigue among Site Reliability Engineering (SRE) teams has reached a breaking point, with responders drowning in thousands of weekly notifications where only 3% genuinely warrant attention. This massive volume of noise—driven by fragmented monitoring tools and rigid, threshold-based alerting—stifles innovation, spikes on-call burnout, and compromises system reliability. Fortunately, AI-powered observability and AIOps platforms are transforming incident management. By unifying telemetry across metrics, logs, and traces, intelligent systems can correlate signals, execute automated root cause analysis, and trigger self-healing remediation. This shift reduces alert volumes by up to 95% and slashes mean time to resolution (MTTR) by 40–58%, allowing engineers to pivot from reactive firefighting to proactive reliability engineering.
5 Ways Agentic AI is Redefining DevOps Architecture for Self-Healing CI/CD Systems
The era of the flaky test as a simple annoyance is over. As enterprises shift from deterministic applications to agentic AI, flakiness has evolved into a structural bottleneck for traditional CI/CD pipelines reliant on rigid, binary assertions. Because AI agents produce “Y-like” rather than exact results, DevOps architecture must fundamentally change. This article explores the transition from simple pipeline automation to true autonomy—detailing how multi-agent networks utilize predictive failure detection, self-healing test repair, autonomous incident remediation, and adaptive security scanning to create pipelines that actively problem-solve and adapt to code changes in real time.
JFrog Report Surfaces Need for Rapid DevSecOps Change in AI Era
A report published by JFrog finds that cybercriminals are now increasingly targeting the artificial intelligence (AI) tools and platforms used by application development teams. Based on an analysis of 18.2 billion artifacts managed via the JFrog Platform, security researchers discovered 969 AI agent skills carrying high-impact payloads in addition to 495 malicious AI models on […]
On-Call: The Silent Force Shaping Engineering Culture
There is a silent force shaping engineering culture inside every technology organization. It affects productivity, team morale, psychological safety, and long-term retention. And yet, it is rarely discussed in executive meetings or reflected in meaningful KPIs. That force is on-call. On-call is one of the most direct touchpoints engineers have with the reality of the […]
Why DORA Metrics Look Different When AI Is Part of Your Development Workflow
DORA metrics have been a reliable compass for engineering teams for over a decade. Deployment frequency, lead time for changes, change failure rate, mean time to recovery, and reliability give teams a shared language for talking about delivery performance. The research behind them is solid, the benchmarks are well-established, and most engineering leaders know what […]