Agentic AI for DevOps Engineers: Building autonomous CI/CD, infrastructure, and operations workflows
Trevoir Williams
Synopsis "Agentic AI for DevOps Engineers: Building autonomous CI/CD, infrastructure, and operations workflows"
Master Agentic AI for DevOps with hands-on guidance to automate CI/CD, infrastructure, observability, incident response, and cloud operations using AI agents and modern DevOps tools A practical, hands-on guide to integrating AI into real-world DevOps workflows, with a strong focus on testing, troubleshooting, and maintaining deterministic controls around AI systems. Wayne Anderson, Managing Director, Cloud Optimization and Cybersecurity, BDO USA A pragmatic guide to AI-enabled DevOps that balances faster delivery with security, governance, human oversight, and controls for risks such as data leakage and hallucinated code. Christophe Foulon, Principal vCISO and AI Governance Lead Key Features Build autonomous CI/CD, infrastructure, and operations workflows using AI agents Learn AI-driven automation for observability, incident response, and cloud operations Implement real-world Agentic AI solutions with DevOps tools, LLMs, and modern platforms Book Description Agentic AI for DevOps is a practical, hands-on guide to building autonomous DevOps workflows powered by AI agents, LLMs, and intelligent automation systems. The book shows you how to modernize software delivery and cloud operations by integrating AI into CI/CD pipelines, infrastructure automation, observability, incident response, and platform engineering. Through real-world projects and demonstrations, the book explores the use of AI copilots, orchestration frameworks, cloud-native tooling, and DevOps platforms to create scalable and production-ready autonomous systems. The book also covers prompt engineering, AI workflow orchestration, security, governance, and best practices for building reliable AI-powered DevOps environments. By the end of the book, you’ll be able to confidently build, deploy, and manage AI-driven DevOps systems that improve speed, reliability, scalability, and operational efficiency. What you will learn Build a practical foundation in Generative AI for DevOps Apply AI across GitHub, Azure DevOps, and CI/CD workflows Implement AI with guardrails, governance, and enterprise awareness Evaluate agentic AI for advanced DevOps scenarios Understand how agentic AI, tools, memory, and MCP extend DevOps automation Use AI to improve code, pipelines, infrastructure as code, and documentation Who this book is for This book is designed for DevOps engineers, platform engineers, SREs, cloud architects, automation specialists, and software developers who want to leverage Agentic AI to automate and optimize modern DevOps workflows. It is ideal for professionals looking to build autonomous CI/CD pipelines, AI-driven infrastructure automation, intelligent monitoring systems, self-healing operations, and scalable cloud-native workflows using AI agents, LLMs, and modern DevOps platforms. Table of Contents Generative AI Concepts for DevOps Practical Applications of Generative AI in DevOps DevOps AI Tools, Governance, and Enterprise Readiness Integrating Generative AI Into DevOps Pipelines Agentic AI for CI/CD Failure Triage and PR Quality Assessment Agentic AI for Advanced DevOps Scenarios: Memory and MCP Multi-Agent Incident Response and Agent Observability Conclusion and Next Steps: Applying Generative AI to DevOps Responsibly
