PromptOps: From YAML to AI
PromptOps: From YAML to AI
The Ultimate DevOps Prompt Cheatsheet
About the Book
For the modern DevOps professional, the gap between an idea and its implementation is filled with verbose YAML, complex configuration, and repetitive boilerplate. PromptOps: From YAML to AI introduces a new, more efficient workflow that treats Artificial Intelligence not as a replacement for your expertise, but as a powerful co-pilot to augment it.
This book provides a practical guide for engineers to transition from being builders of complex systems to directors of them. It moves beyond theory to offer a hands-on approach, centered on the C.R.A.F.T. framework (Context, Role, Action, Format, Tone)—a clear and repeatable methodology for giving precise instructions to an AI to get production-quality results, the first time.
Inside, you will learn to:
- Generate Infrastructure as Code for Terraform, CloudFormation, and Ansible by describing infrastructure in plain English.
- Master CI/CD pipelines for GitHub Actions and GitLab CI, eliminating the toil of writing YAML from scratch.
- Perfect containerization by generating optimized, multi-stage Dockerfiles and complete Kubernetes manifest sets.
- Accelerate daily tasks by creating robust scripts for automation, health checks, and backups.
- Improve incident response by using your AI assistant to analyze logs, draft communications, and structure post-mortems.
- Codify and scale your team's knowledge by building a shared, version-controlled library of "Prompts-as-Code."
PromptOps is written for the professional SRE, platform engineer, or developer who understands that the future of operations lies in leveraging automation at a higher level. This book will equip you with the skills to reduce complexity, increase consistency, and focus on the high-level architectural challenges that deliver real business value.
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Table of Contents
- Foreword
- Brief of Contents
- Introduction: The Next Evolution of DevOps
- Chapter 1: The Inevitable Shift: Why Prompting is a Core DevOps Skill
- Moore’s Law for Models
- From “Infrastructure as Code” to “Infrastructure as a Conversation”
- The Key Benefits
- Case Study: How a Simple Prompt Saved 4 Hours of Manual Work
- Chapter 2: Prompt Engineering 101 for the Technical Mind
- The C.R.A.F.T. Framework
- Good vs. Bad Prompts: An Interactive Example
- Chapter 3: Your AI-Powered Toolkit: Setting Up for Success
- Choosing Your Language Model
- Essential Tools: Where the Conversation Happens
- Building Your First “Prompt Snippet” Library
- Chapter 4: Generating Infrastructure as Code (IaC)
- The Core Pattern: From Description to Definition
- Terraform, CloudFormation, & Ansible: From Prompt to Production
- A Note on Secrets and Sensitive Data
- Refining and Debugging with Follow-Up Prompts
- Deep Dive: The “Why” Behind IaC Best Practices
- Chapter 5: Mastering the CI/CD Pipeline
- The End of YAML Boilerplate
- GitHub Actions & GitLab CI: Creating Complex Workflows
- Advanced Pipeline Patterns
- Chapter 6: Containerization Perfected: Docker & Kubernetes
- Writing Optimized, Multi-Stage Dockerfiles
- Generating Kubernetes Manifests
- Prompting for Helm Chart Creation
- Debugging with Prompts: Your AI First Responder
- Chapter 7: The Observability Assistant
- Log Analysis: Finding the Signal in the Noise
- Query Generation: From Questions to Queries
- Dashboard Design: From Idea to Visualization
- Chapter 8: Scripting and Automation
- Generating Scripts for Backups, Health Checks, and Data Processing
- Refactoring and Documenting Existing, Complex Scripts
- Using Prompts to Add Error Handling and Logging
- Chapter 9: Incident Management and Communication
- Summarizing Alerts and Incident Timelines
- Drafting Clear, Concise Stakeholder Communications
- Generating Root Cause Analysis (RCA) Document Templates
- Chapter 10: Building a Team-Wide Prompt Library
- From Personal Snippets to a Shared Repository (“Prompt-as-Code”)
- Best Practices for Creating Reusable and Maintainable Prompt Templates
- Chapter 11: The Pitfalls: Security, Hallucinations, and Validation
- The #1 Rule: Never Paste Secrets into a Public LLM
- Strategies for Validating AI-Generated Code
- The Importance of Human Oversight: The AI is Your Co-Pilot, Not the Pilot
- Chapter 12: Learning and Mastering New Technologies with PromptOps
- The Traditional Learning Challenge
- AI as Your Personal Technical Tutor
- The C.R.A.F.T. Framework for Learning
- Practical Learning Strategies
- Case Study: Learning Kubernetes from Scratch
- Learning Emerging Technologies
- Building Deep Understanding Through Teaching
- Learning Anti-Patterns to Avoid
- Building a Personal Learning System
- The Future of Technical Learning
- Conclusion: Becoming a Perpetual Learner
- Chapter 13: The Future: From Prompt-Driven to Agent-Driven (PromptOps)
- An Introduction to AI Agents
- A Look at the Emerging Tools
- Preparing Your Skills for a Future of Autonomous Operations
- Conclusion: Your Journey as a Prompt-Driven Engineer
- Foreword
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