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The Aiops Book

by · github.com/hoalongnatsu/the-aiops-book

Learn to build AI-powered infrastructure automation with MCP servers and AI agents in Go. Production-ready patterns for DevOps engineers to create intelligent AWS automation systems.

Unclaimed last commit 10 months ago mcpartificial-intelligencegogolangdevtoolsdevopsaws
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About The Aiops Book

The Aiops Book is an MCP server published by hoalongnatsu in the Developer Tools category: learn to build AI-powered infrastructure automation with MCP servers and AI agents in Go. Production-ready patterns for DevOps engineers to create intelligent AWS automation systems. It has been installed 0 times through Conduid.

The repository has 13 stars and 7 forks, with the last commit 10 months ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues (0) before depending on it in production.

Install

Install
npx the-aiops-book

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README

The AIOps Book

Master AI-powered infrastructure automation with this hands-on guide to building production-ready MCP servers and AI agents in Go. Transform from manual AWS operations to intelligent automation that understands your environment and makes smart decisions while keeping humans in control.

Book Structure & Content

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

Part II: Building MCP Servers

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

Chapter 8: Refactoring for Production-Ready Architecture

  • Understanding the Current Architecture's Limitations
  • Refactoring Goals and Vision
  • Key Refactoring Steps
  • Challenges and Solutions
  • Preparation for Chapter 9
  • Conclusion

Chapter 9: GitHub Copilot and MCP Integration for Infrastructure Automation

  • GitHub Copilot and MCP
  • VS Code MCP Configuration Deep Dive
  • Real-World Scenario: Three-Tier Application with GitHub Copilot
  • Understanding Copilot's AI Decision Process
  • Advanced Copilot Integration Patterns
  • Debugging and Troubleshooting MCP with GitHub Copilot
  • Chapter Summary

Part III: AI Agents for DevOps

Chapter 10: AI Agents Architecture

  • From Stateless Tools to Stateful Agents
  • AI Agent Foundation
  • Agent Architecture Patterns
  • Agent Components Deep Dive
  • Enterprise Agent Considerations
  • What You've Learned
  • What's Next

Chapter 11: Understand What You Will Build

  • The Evolution from Automation to Intelligence
  • Core Principles of AI Infrastructure Agents
  • AI Agent Architecture Overview
  • The Agent Execution Flow
  • What You Will Build
  • The Strategic Advantage
  • What's Next

Chapter 12: Introduction to LangChain Framework

  • What is LangChain?
  • Why LangChain for Infrastructure Agents?
  • LangChain Core Concepts
  • Mapping LangChain to Your Agent Architecture
  • Agent Patterns in LangChain
  • LangChain in Go vs Python
  • Why This Matters for Infrastructure Automation
  • What You've Learned
  • What's Next

README mirrored from the source repository 4 months ago. The original is authoritative.

Questions

About The Aiops Book

How do I install The Aiops Book?

Run npx the-aiops-book, then add the server to your MCP client's configuration. Conduid has recorded 0 installs, so the command is known to work with current clients.

Is The Aiops Book safe to use with an AI agent?

Its trust score is 51 out of 100 (fair). It passes 0 of 1 static security checks; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is The Aiops Book still maintained?

The last commit was 10 months ago, with 0 open issues. That's long enough that you should check whether the maintainer is responding to issues before depending on it.