Latest Articles
Is Java Enterprise Ready for AI? Absolutely
AI is transforming software engineering. For enterprise Java developers, the key question is whether Java and Jakarta EE are prepared to integrate AI into enterprise applications. The answer is yes. Java and ...
CI/CD for AI-Enabled Applications: Why Traditional Deployment Pipelines Need to Evolve
Prem Kumar Gadhanki | | artificial intelligence, CI/CD, continuous delivery, devops, MLOps, software deliveryTraditional CI/CD pipelines are optimized around a familiar assumption: source code changes, automated tests validate the change, a build artifact is produced, and the application is promoted through environments. AI-enabled applications complicate ...
The AI Agent Race Is On. But Are We Watching the Right Race?
Claude Code, OpenAI Codex, GitHub Copilot, Cursor and a growing field of challengers are competing to define the future of software development. A new Techstrong special report examines who is ahead, how ...
Report Shines Spotlight on 91 Vulnerabilities Fixed in Latest Update to Spring Framework
Mike Vizard | | AI cybersecurity, AI vulnerabilities, application security, Broadcom, CVEs, devsecops, Java security, open source security, open source vulnerabilities, patch management, security automation, software components, Software Supply Chain, sonatype, Spring framework, Spring vulnerabilities, technical debt, virtual patching, vulnerability managementSonatype says 91 Spring vulnerabilities affecting more than 209,000 software components highlight how AI is accelerating vulnerability discovery and creating a new patching challenge for DevSecOps teams ...
Why “Tokenmaxxing” Was Always the Wrong Way for Developers to Measure AI Productivity
Drew Thompson | | ai, AI Development, AI security, application security, developer productivity, software developmentThe term "tokenmaxxing" left the developer lexicon just as quickly as it arrived, and like most viral technology concepts, it means different things depending on who's using it. In practice, the term ...
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 ...
