Business of DevOps
How to Build a Durable Change-Control Gate for AI Agents
Daniel Martin | | agentic AI, AI agents, AI automation, AI Governance, AI safety, approval workflows, change control, devops, durable workflows, human-in-the-loop, idempotency, LangGraph, NIST AI RMF, policy enforcement, production deployment, release controls, tool-using agents, workflow governanceAI agents that trigger real-world changes need more than confidence scores. A durable change-control gate should recheck policy, require approval for consequential actions, enforce idempotency and verify the result before retrying ...
Production Validation: The Missing Layer in Enterprise Releases
Kawaljeet Singh Chadha | | auditability, business validation, business-critical systems, change management, data quality, deployment controls, DevOps governance, enterprise devops, Enterprise software, exception-handling, operational approval, production assurance, production readiness, production validation, reconciliation, regulated environments, release governance, release management, release readiness, software testingProduction validation adds a critical business-control layer between testing and deployment, combining data checks, exception review, approvals, reconciliation and operational readiness before a release reaches production ...
The Missing Runtime for Long-Running AI Agents
Anuj Kapoor | | agent governance, agent orchestration, agent runtime, AI agents, AI observability, AI resiliency, Azure AI Foundry, Azure Durable Functions, devops, distributed systems, durable AI agents, durable workflows, Enterprise AI, human-in-the-loop, long-running AI agents, multi-agent systems, platform engineering, stateful AI, workflow orchestrationEnterprise AI agents need more than stronger models. They need durable execution environments that can coordinate multi-step workflows, survive failures, pause for human review and resume reliably after disconnects or delays. AI ...
Automated Diagnosis Isn’t Automated Understanding: What Postmortems Teach Us About Building Trustworthy Incident AI
Jyostna Seelam | | AI incident response, AI observability, AI reliability, AIOps, alert correlation, automated incident response, causal reasoning, dependency graphs, devops, Engineering leadership, human-in-the-loop, incident diagnosis, incident management, LLM operations, non-deterministic systems, on-call engineering, postmortems, RAG systems, root cause analysis, SREAI incident tools can reduce alert noise, but real root-cause diagnosis requires causal reasoning, live dependency context, uncertainty handling and strong postmortem data ...
AI Can Generate Your Infrastructure. Can Your CI/CD Pipeline Trust It?
Oreoluwa Omoike | | AI code vulnerabilities, AI coding assistants, AI-generated code, AI-generated infrastructure, Checkov, CI/CD security, Conftest, devsecops, IaC security, infrastructure as code, infrastructure security, Kubernetes security, OPA, platform engineering, policy as code, provenance tracking, secret scanning, secure CI/CD, Terraform security, tfsec, Trivy, TruffleHogAI-generated infrastructure code is exposing a growing security gap, pushing platform teams to add stronger automated gates, provenance tracking and human review before Terraform, Kubernetes and CI/CD changes reach production ...
Your AI Coding Budget Is Becoming a Variable Cloud Bill
Carla Castillo | | agentic coding, AI coding assistants, AI coding costs, AI cost management, AI credits, AI developer tools, AI Governance, cloud economics, cost per developer, developer productivity, devops, engineering spend, FinOps for AI, GitHub Copilot, model mix, platform engineering, premium models, SaaS budgeting, token billing, usage based billingAI coding assistants are becoming a variable, usage-based engineering cost, forcing platform and DevOps teams to apply FinOps practices to models, credits, utilization and multi-vendor spend ...
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 ...
Elevating Technical Documentation: Using Predictive AI to Standardize Visual Knowledge Bases
Nazim Ghori | | AI documentation, AI visual validation, architecture diagrams, CI/CD documentation, computer vision, developer documentation, developer experience, devops automation, DevOps documentation, documentation automation, documentation drift, documentation quality, documentation quality gates, Git workflows, knowledge bases, OCR, predictive AI, screenshot validation, technical documentation, visual validationEvery release changes documentation alongside the code. Developers depend on that documentation during implementation, maintenance and troubleshooting. A diagram becomes misleading once services are renamed or integrations change without a corresponding documentation ...
Adronite Unveils AI Coding Tool Based on Embedded Context Engine
Mike Vizard | | ACE, Adronite, Adronite Context Engine, AI code generation, AI coding assistants, AI coding tool, AI-generated code, code review, codebase context, Codistry, developer tools, devops, open-weight AI models, software development, token efficiencyAdronite launches Codistry, an AI coding tool that uses a context engine to map codebases, reduce token usage and generate more production-ready code ...
The Agent Proposes, the Pipeline Disposes: Controls for AI-Authored Change
Veera Ravindra Divi | | agent permissions, agentic coding, AI change control, AI code review, AI coding agents, AI Governance, AI pull requests, AI software development, AI-authored code, AI-generated code security, autonomous coding agents, bounded-write agents, change-budget gates, CI/CD security, human-in-the-loop, in-toto, independent evals, least-privilege, policy as code, protected paths, provenance attestation, provenance verification, Secure DevOps, signed attestations, Sigstore, SLSA, Software Supply Chain Security, staged autonomyWhen agents write code and open pull requests faster than humans can read them, ‘the diff looked fine’ stops being a control. The durable controls live outside the agent’s reasoning loop ...
What You Cannot See Will Break Your LLM App: A Practitioner Guide to Production Observability
Gourav Singla | | AI monitoring, AI observability, AI quality monitoring, automated AI evaluation, Distributed Tracing, finish reason, hallucination monitoring, LLM cost observability, LLM latency, LLM monitoring, LLM observability, LLM tracing, model-graded evaluation, OpenTelemetry GenAI, OTel GenAI, production AI reliability, production LLMs, prompt failures, prompt regression, provider monitoring, quality drift, token budget alerting, token cost monitoringTraditional application observability was built around a simple mental model: Your code runs, metrics come out and when something breaks, the logs tell you why. Large language models (LLMs) break that model ...
Fast-Moving Shai-Hulud Attack Infects npm Packages with 2 Billion Monthly Downloads
Jeff Burt | | Aikido Security, AWS, credential theft, GitHub Actions, HashiCorp Terraform, npm malware, Shai-Hulud worm, supply chain attackResearchers at Aikido Security and Endor Labs are tracking a fast-spreading supply-chain attack that is compromising a wide range of npm software packages that combined have more than 2 billion installs a ...
