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DevOps → DevSecOps → AI SecOps → AIOps Career Bible

The Complete Self-Contained Guide to Mastering Modern DevOps, Security, and AI Operations

License: MIT PRs Welcome

🚀 Quick Navigation

Section Quick Links
Start Here Mindset • 6-Month DevOps Roadmap • Full Career Map
Fundamentals Linux • Git • Networking • Scripting
Core DevOps Docker • Kubernetes • CI/CD • Terraform • AWS
Security DevSecOps Overview • Container Security • Secrets Management
AI Security AI SecOps Overview • LLM Security • Prompt Injection Defense
AIOps AIOps Overview • Anomaly Detection • Automated Remediation
Practice DevOps Labs • Projects • Interview Prep
Reference Cheat Sheets • Troubleshooting

📚 Overview

This repository is your complete, internet-independent, production-grade guide to becoming an elite DevOps, DevSecOps, AI SecOps, or AIOps engineer. It contains the equivalent of 3+ years of real-world experience, from fundamentals to advanced specialization paths.

🎯 What You'll Learn

  • DevOps Fundamentals: CI/CD, containers, Kubernetes, infrastructure automation
  • Production Operations: Monitoring, observability, SRE practices, on-call excellence
  • DevSecOps: Security scanning, secrets management, supply chain security
  • AI SecOps: LLM security, prompt injection defense, model security
  • AIOps: Anomaly detection, automated remediation, intelligent observability
  • Platform Engineering: Internal Developer Platforms, golden paths, developer experience

🚀 Who This Is For

  • Beginners starting their DevOps journey
  • Mid-level engineers looking to specialize
  • Senior engineers preparing for FAANG/MAANG interviews
  • Career switchers transitioning into DevOps
  • Anyone wanting a complete, self-contained learning resource

📖 Repository Structure

🗺️ Career Roadmaps

🎓 Foundation

⚙️ DevOps

🏗️ Platform Engineering

🔒 DevSecOps

🤖 AI SecOps

🧠 AIOps

🛠️ Hands-On Labs

🚀 Projects

💼 Interview Preparation

📋 Cheat Sheets

🗺️ Roadmaps

🗺️ Learning Paths

Path 1: DevOps Engineer (6-12 months)

  1. Start with Foundation - Master Linux, networking, Git, scripting
  2. Progress through DevOps - Docker, Kubernetes, CI/CD, AWS
  3. Complete DevOps Labs and DevOps Projects
  4. Study DevOps Interview and Kubernetes Interview

Path 2: DevSecOps Engineer (12-18 months)

  1. Complete DevOps path first
  2. Deep dive into DevSecOps - All security topics
  3. Practice Security Labs and SecOps Projects
  4. Prepare with DevSecOps Interview

Path 3: AI SecOps Specialist (18-24 months)

  1. Master DevSecOps fundamentals
  2. Study AI-SecOps - LLM security, prompt injection, model security
  3. Complete AI SecOps Labs and AI Security Projects
  4. Interview prep: AI Security Interview

Path 4: AIOps Engineer (18-24 months)

  1. Strong DevOps + observability background
  2. Learn AIOps - Anomaly detection, automated remediation
  3. Practice AIOps Labs and AIOps Projects
  4. Interview prep: AIOps Interview

Path 5: Platform Engineer (24-30 months)

  1. Senior DevOps experience required
  2. Study Platform Engineering - IDPs, Backstage, golden paths
  3. Complete Platform Engineering Projects
  4. Focus on developer experience and infrastructure standards

🎓 How to Use This Repository

For Beginners

  1. Read DevOps Mindset first
  2. Follow 6-Month DevOps Roadmap step-by-step
  3. Complete every lab in Hands-On
  4. Build projects from Projects
  5. Use CheatSheets for quick reference

For Intermediate Engineers

  1. Identify gaps in your knowledge
  2. Deep dive into specific topics
  3. Complete advanced labs and projects
  4. Study interview questions in Interview
  5. Focus on production practices

For Interview Preparation

  1. Review all Interview files
  2. Practice System Design scenarios
  3. Study CheatSheets for quick recall
  4. Complete Coding Tasks
  5. Review Troubleshooting Guide for on-call scenarios

📋 Content Standards

Every file in this repository includes:

  • ✅ Deep technical explanations
  • ✅ Real-world examples and use cases
  • ✅ CLI commands with expected outputs
  • ✅ YAML/JSON manifests and configurations
  • ✅ Architecture diagrams (ASCII + Mermaid)
  • ✅ Production best practices
  • ✅ Troubleshooting guides
  • ✅ Security considerations
  • ✅ Hands-on exercises
  • ✅ Interview questions

🔥 Key Features

Self-Contained

  • No external dependencies or links
  • All information needed is within this repo
  • Works offline completely

Production-Grade

  • Real-world scenarios and examples
  • Industry best practices
  • FAANG/MAANG-level content
  • Battle-tested approaches

Comprehensive

  • 100+ detailed guides
  • 3+ years of experience condensed
  • Covers all specializations
  • Interview-ready content

Hands-On

  • Practical labs for every topic
  • Real-world projects
  • Step-by-step tutorials
  • Troubleshooting exercises

🛠️ Prerequisites

While this guide is comprehensive, having access to:

  • A Linux machine or VM (Ubuntu 20.04+ recommended)
  • AWS account (free tier works)
  • GitHub account
  • Docker Desktop or Docker Engine
  • Kubernetes cluster (minikube, kind, or cloud)

Will help you practice the hands-on labs.

📝 Contributing

This is a living document. Contributions are welcome! Please:

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Submit a pull request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

This repository is the result of years of experience in DevOps, SRE, DevSecOps, and AI operations. It's designed to be the single source of truth for anyone looking to master these fields.

🎯 Success Metrics

After completing this guide, you should be able to:

  • ✅ Design and implement production-grade CI/CD pipelines
  • ✅ Deploy and manage Kubernetes clusters at scale
  • ✅ Implement comprehensive security practices
  • ✅ Build and secure AI/ML systems
  • ✅ Design intelligent observability solutions
  • ✅ Build internal developer platforms
  • ✅ Debug complex production issues
  • ✅ Pass FAANG/MAANG-level interviews

🚀 Quick Start

  1. Clone this repository

    git clone https://github.com/yourusername/devopsbible.git
cd devopsbible

  2. Choose your path

  3. Follow a roadmap

  4. Practice, practice, practice

    • Theory without practice is incomplete
    • Complete every lab
    • Build every project
    • Study every interview question

📞 Support

For questions, issues, or contributions:

  • Open an issue on GitHub
  • Check existing issues for solutions
  • Review the troubleshooting guides

Remember: This is not a quick-fix guide. Mastery requires dedication, practice, and real-world experience. Use this repository as your foundation, but always continue learning and adapting.

Good luck on your DevOps journey! 🚀