Chaos Engineering

Table of contents

1. I. Introduction
2. 1. Why Do Chaos Engineering?
   1. How Does Chaos Engineering Differ from Testing?
   2. It’s Not Just for Netflix
   3. Prerequisites for Chaos Engineering
3. 2. Managing Complexity
   1. Understanding Complex Systems
   2. Example of Systemic Complexity
   3. Takeaway from the Example
4. II. The Principles of Chaos
   1. Experimentation
   2. Advanced Principles
5. 3. Hypothesize about Steady State
   1. Characterizing Steady State
   2. Forming Hypotheses
6. 4. Vary Real-World Events
7. 5. Run Experiments in Production
   1. State and Services
   2. Input in Production
   3. Other People’s Systems
   4. Agents Making Changes
   5. External Validity
   6. Poor Excuses for Not Practicing Chaos
      1. I’m pretty sure it will break!
      2. If it does break, we’re in big trouble!
   7. Get as Close as You Can
8. 6. Automate Experiments to Run Continuously
   1. Automatically Executing Experiments
   2. Automatically Creating Experiments
9. 7. Minimize Blast Radius
10. III. Chaos In Practice
11. 8. Designing Experiments
    1. 1. Pick a Hypothesis
    2. 2. Choose the Scope of the Experiment
    3. 3. Identify the Metrics You’re Going to Watch
    4. 4. Notify the Organization
    5. 5. Run the Experiment
    6. 6. Analyze the Results
    7. 7. Increase the Scope
    8. 8. Automate
12. 9. Chaos Maturity Model
    1. Sophistication
    2. Adoption
    3. Draw the Map
13. 10. Conclusion
    1. Resources