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Agentic DevOps Engineering: Build AI-Powered DevOps Agents with Python, Automate CI/CD Pipelines, and Manage Cloud Infrastructure
What if your DevOps systems could do more than execute scripts? What if AI agents could investigate failed deployments, monitor infrastructure, identify problems, and recommend solutions before small issues become costly outages?
Modern DevOps teams face growing pressure to deliver software faster, maintain reliable infrastructure, and resolve technical problems with fewer manual tasks. Traditional automation helps, but AI-powered agents introduce a new level of intelligent monitoring, investigation, and workflow coordination.
Agentic DevOps Engineering is a practical, hands-on guide to building AI-powered DevOps agents with Python and integrating them into real-world development and infrastructure workflows.
Whether you're a DevOps engineer, cloud professional, Python developer, software engineer, or IT automation enthusiast, this book provides the knowledge and practical examples needed to understand, build, secure, and deploy intelligent DevOps automation systems.
WHAT YOU'LL LEARN INSIDE:
Agentic DevOps Fundamentals: Understand how AI agents work, make decisions, use tools, and support modern DevOps operations.
Building AI Agents with Python: Develop practical agents using Python, AI model APIs, structured tool calling, and controlled execution.
Intelligent CI/CD Automation: Integrate AI agents with GitHub Actions to investigate pipeline failures and improve software delivery workflows.
Docker and Kubernetes Automation: Inspect containers, monitor workloads, troubleshoot deployment issues, and interact with orchestration APIs.
Cloud Infrastructure Management: Work with Terraform, Infrastructure as Code, and Python cloud SDKs to automate infrastructure inspection.
AI-Powered Monitoring: Collect logs, analyze system events, investigate incidents, and generate actionable reports.
Security and Access Control: Protect credentials, restrict tool permissions, prevent unsafe operations, and implement approval workflows.
Testing and Deployment: Test agent behavior, package applications with Docker, and monitor reliability, performance, and costs.
Complete Hands-On Project: Build an integrated Agentic DevOps system connecting Python agents, CI/CD monitoring, and infrastructure tools.
WHY THIS BOOK MATTERS
This book goes beyond theory. You'll work with practical Python examples, real-world DevOps scenarios, and structured exercises that demonstrate how intelligent automation works.
You'll learn to reduce repetitive troubleshooting, improve infrastructure visibility, strengthen operational security, and build reliable AI-assisted workflows.
DevOps is evolving, and AI-powered automation is becoming an increasingly valuable engineering skill. Understanding how to build and control these systems can help you prepare for more advanced responsibilities in cloud engineering, platform operations, and software delivery.
Stop relying entirely on manual investigations and disconnected automation tools.
Get your copy of Agentic DevOps Engineering today and start building secure, intelligent, and practical DevOps automation systems with Python!
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