The AIOps Book
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The AIOps Book

From Manual Operations to AI-Powered Infrastructure

About the Book

Transform your infrastructure operations with AI-powered automation that actually works in production. This comprehensive guide teaches DevOps engineers, SREs, and platform architects how to build intelligent systems using the Model Context Protocol (MCP) and AI agents with Go.

Stop copying configuration files into ChatGPT and start building AI assistants that understand your AWS environment directly. Learn to create MCP servers that give AI systems real-time access to your infrastructure, develop agents that can provision complete environments from natural language descriptions, and implement secure automation workflows that augment human expertise without replacing it.

Written by a practicing DevOps engineer for practitioners, this book focuses on production-ready solutions rather than theoretical concepts. You'll build working systems from day one: MCP servers that integrate with AWS APIs, AI agents that can analyze deployment failures and suggest specific fixes, and complete automation workflows that handle the repetitive tasks while keeping humans in control of critical decisions.

Every chapter includes working Go code examples, real-world scenarios, and practical patterns you can adapt to your environment. The companion GitHub repository provides complete implementations that you can deploy and extend immediately.

Whether you're automating your first infrastructure task with AI or designing enterprise-scale AIOps platforms, this book gives you the knowledge and tools to build systems that are both intelligent and reliable. Learn to leverage AI's pattern recognition and reasoning capabilities while maintaining the security, auditability, and control that production environments require.

The future of infrastructure operations isn't about replacing DevOps engineers with AI—it's about augmenting human expertise with tools that can handle complexity at scale. Start building that future today.

About the Author

Quan Huynh
Quan Huynh

I am a DevOps Lead at Vikki Digital Bank with extensive experience in designing, building, and managing mission-critical infrastructure for digital banking products on Amazon Web Services (AWS). My professional journey has been deeply rooted in the financial sector, where security, resilience, and scalability are paramount.

As a founder of DevOpsVN, my goal is to empower the tech community by simplifying complex concepts and offering actionable, real-world solutions. Through my writing, I strive to bridge the gap between theory and practice, helping others navigate the ever-evolving landscape of modern technology.

Table of Contents

    • Preface
      • Who This Book Is For
      • What You’ll Build
      • How This Book Is Organized
      • A Note on the Rapidly Evolving Landscape
      • Acknowledgments to the Community
    • Part I: Foundation
    • Chapter 1: The AIOps Revolution
      • The Limits of Traditional Automation
      • What AIOps Really Means
      • The Infrastructure Context Problem
      • Enter MCP and AI Agents
      • Real-World Impact and Case Studies
      • Why This Matters Now
      • What You’ll Learn in This Book
    • Chapter 2: AI Fundamentals for DevOps Engineers
      • Understanding Large Language Models for Infrastructure Work
      • The Context Window and Memory Limitations
      • Prompt Engineering for Infrastructure Automation
      • AI Capabilities and Limitations in Operations
      • Security Considerations for AI-Powered Infrastructure
      • Integration Patterns with Existing Tools
      • Choosing the Right AI Models and Providers
      • Building Reliable AI Systems
      • What’s Next
    • Chapter 3: Model Context Protocol Deep Dive
      • What MCP Is and Why It Matters
      • MCP Architecture and Core Concepts
      • Protocol Specifications and Communication Patterns
      • MCP vs REST APIs and GraphQL
      • Real-World MCP Use Cases in DevOps
      • The MCP Ecosystem and Tooling
      • Security and Trust in MCP Implementation
      • Protocol Evolution and Future Directions
      • What’s Next
    • Chapter 4: Setting Up Your Development Environment
      • Go Development Environment for MCP
      • AWS CLI and SDK Configuration
      • AI Tools Integration
      • What’s Next
    • Chapter 5: Your First MCP Server in Go
      • Project Structure and Dependencies
      • Basic MCP Protocol Implementation
      • AWS SDK Integration
      • Resource Discovery and Formatting
      • Testing Your MCP Server
      • What’s Next
    • Chapter 6: MCP Tools for Infrastructure Actions
      • Understanding MCP Tools vs Resources
      • Project Structure for Tools
      • Implementing MCP Tools
      • Extending the AWS Client
      • Tool Registration in MCP Server
      • Real-World Example: Complete AI-to-Infrastructure Flow
      • Chapter Summary
    • Chapter 7: Advanced AWS Operations
      • The Production Infrastructure
      • AWS Infrastructure Fundamentals
      • Enhanced MCP Server Architecture
      • Extended Project Structure
      • Core Parameter Structures
      • VPC and Networking Tools Implementation
      • Auto Scaling Group Tools Implementation
      • Application Load Balancer Tools Implementation
      • RDS Tools Implementation
      • Tool Registration and MCP Integration
      • Real-World Example: Complete Production Deployment
      • Chapter Summary
      • What’s Next

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