Latest Articles
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 ...
Beyond Log Search: What We Learned Building a RAG-Based Incident Diagnosis System
Abhimanyu Garg | | AI for SRE, AI hallucinations, AI incident diagnosis, AIOps, devops, devops automation, FAISS, incident management, incident remediation, incident response, knowledge management, knowledge retrieval, LLM grounding, LLM incident response, observability, postmortems, production AI, RAG AIOps, re-ranking, retrieval-augmented generation, root cause analysis, Runbooks, semantic search, SREA RAG-based AIOps framework can cut incident diagnosis time by grounding LLM reasoning in real runbooks, tickets and postmortems, improving root-cause accuracy while giving SREs source-backed answers they can trust ...
Scalable Jenkins Management: Empowering Enterprises With Centralized Control for 150+ Instances
Thrivikram Eskala | | ansible, ArgoCD, AWS, azure, CI/CD Automation, developer platform, devops automation, ELK stack, gitops, grafana, Helm, Jenkins, Jenkins administration, Jenkins backups, Jenkins control plane, Jenkins fleet, Jenkins management, Jenkins observability, Jenkins rollback, Jenkins upgrades, kubernetes, multi-cloud CI/CD, platform engineering, Prometheus, self-service platformA centralized Jenkins control plane can reduce fleet sprawl, automate upgrades and backups, improve observability, and give application teams safe self-service across large multi-cloud CI/CD estates ...
Preparing Infrastructure for the Next Phase of Agentic AI
Gretchen Stewart | | agent orchestration, agentic AI, AI agents, AI data architecture, AI infrastructure, AI modernization, AI observability, AI resource management, AI workflows, AI workload management, autonomous agents, cloud infrastructure, data movement, federal agencies, government AI, government IT, human-in-the-loop, hybrid infrastructure, infrastructure modernization, multi-agent systems, on-premises AI, public sector AIAgentic AI is changing government infrastructure requirements, pushing agencies to rethink workflows, observability, data movement and resource prioritization before investing in new hardware ...
Dash0 Acquires Polar Signals for Continuous Profiling and GPU Visibility
Observability startup Dash0 announced this week that it acquired Berlin-based continuous profiling specialist Polar Signals. The deal adds continuous profiling to SignalStore, Dash0’s OpenTelemetry-native data platform. Continuous profiling has been part of ...
Hackers Target Popular arrayref Rust Crate in Supply-Chain Attack
Jeff Burt | | arrayref, information stealing, North Korea, Rust programming language, software supply chain attacks, StepSecurity, typosquatting, Wiz ResearchSecurity researchers are sorting through a complex, stealthy, and fast-moving supply-chain attack aimed at pushing information-stealing malware by compromising the account of the maintainer of multiple Rust crates and introducing four more ...
Production-Grade AI Eval Systems. What I Learned Putting LLMs on Call
Anjaiah Methuku | | AI evals, AI guardrails, AI observability, AI quality monitoring, AI reliability engineering, AI SRE, AI testing, answer relevance, CI evals, context precision, context recall, faithfulness, hallucination detection, human-in-the-loop, LLM evaluation, LLM judges, LLM reliability, model monitoring, production AI, production-grade AI, RAG evaluation, RAG metrics, regression testing, retrieval-augmented generationProduction-grade AI reliability requires more than uptime and latency. A layered eval system helps teams detect hallucinations, RAG failures and quality regressions before customers do ...
Waterfall 2.0: Controlling LLM-Driven Software Development with Stage-Gated Discipline
Georgy Starikov | | ADRs, Agile vs Waterfall, AI coding, AI development lifecycle, AI Software Engineering, AI-assisted engineering, architecture decision records, combi-shaper, engineering workflows, generative AI development, knowledge corpus, LLM engineering, LLM software development, MCP, Model Context Protocol, software architecture, software testing, system design, Waterfall 2.0Waterfall 2.0 reimagines classic stage-gated software development for the LLM era, combining fast AI generation with structured validation, cheap backtracking and a shared knowledge corpus ...
Why API Test Generation Is a Judgment Problem, Not a Code Generation Problem
Abhishek Saikia | | adaptive test coverage, AI API testing, AI quality engineering, AI test generation, API test generation, API testing, Automated testing, cross-field testing, DevOps Testing, fine-tuning, LLM testing, QA automation, RAG, software testing, test assertions, test coverageWhen we started using large language models for API test generation at KushoAI, the results were impressive on the surface. Tests appeared in seconds. Coverage breadth went up. The team was excited ...
Why Cryptographic Inventory Is the First Step Toward Quantum Readiness
Michael Carter | | CBOM, CI/CD security, crypto-agility, cryptographic dependencies, cryptographic discovery, cryptographic inventory, cryptography bill of materials, devops security, devsecops, Kubernetes security, ML-KEM, NIST PQC migration, post-quantum cryptography, PQC, quantum readiness, Software Supply Chain SecurityPost-quantum readiness starts with visibility. DevOps teams need a continuous cryptographic inventory to map algorithms, keys, certificates, libraries, infrastructure and third-party dependencies before PQC migration begins ...
npm v12 Shuts Down a Popular Malware Trick — But the Threat Isn’t Going Away
For years, one of the easiest ways to sneak malware onto a developer's machine has been to hide in plain sight. Install a package from npm, and any lifecycle script bundled with ...
AI Agents Are Writing Code Faster Than Anyone Can Review It. Tessl Is Betting On Standards To Close That Gap
Every team that has turned coding agents loose on real work has run into the same wall. The agents write fast. They write a lot. And somewhere between the tenth and twentieth ...
