AI-POWERED DEVOPS

Every AI vendor promises "self-healing infrastructure." None of them tell you what actually breaks when you trust an AI agent with production.
You've watched the demos. Autonomous incident response. AI that writes its own runbooks. Infrastructure that fixes itself while you sleep. And you've also watched what happens when an overconfident AI agent makes the wrong call at 3am, because vendor marketing never mentions that part.
AI-Powered DevOps is the practitioner's guide the hype cycle skipped: a clear-eyed, hands-on playbook for engineers who need to actually ship AI into their DevOps and SRE workflows, not just talk about it in a planning meeting.
This isn't theory. It's not another "introduction to AI" book padded with generic explainers. It's a working system, built chapter by chapter, using real tools you already know: Claude, LangGraph, Kubernetes, and the Model Context Protocol, with full, runnable source code for every example.
Inside, you'll learn how to:

• Build AI agents that triage incidents and perform root-cause analysis, with a confidence-scoring model that knows when to escalate instead of guessing
• Apply a 5-stage AIOps maturity model (Stage 0-4) so you know exactly how much autonomy is appropriate at each stage of your pipeline, and where full autonomy is a mistake
• Design monitoring and observability systems where AI augments your SREs instead of replacing their judgment
• Secure AI agents against prompt injection and tool abuse before they touch production
• Govern AI-driven operations for audit, compliance, and cost (FinOps) at enterprise scale
• Integrate AI into CI/CD pipelines without introducing a new class of silent failures