With so many interacting components, the number of things that can go wrong in a distributed system is enormous. You’ll never be able to prevent all possible failure modes, but you can identify many of the weaknesses in your system before they’re triggered by these events. This report introduces you to Chaos Engineering, a method of experimenting on infrastructure that lets you expose weaknesses before they become a real problem.
Members of the Netflix team that developed Chaos Engineering explain how to apply these principles to your own system. By introducing controlled experiments, you’ll learn how emergent behavior from component interactions can cause your system to drift into an unsafe, chaotic state.
- Hypothesize about steady state by collecting data on the health of the system
- Vary real-world events by turning off a server to simulate regional failures
- Run your experiments as close to the production environment as possible
- Ramp up your experiment by automating it to run continuously
- Minimize the effects of your experiments to keep from blowing everything up
- Learn the process for designing chaos engineering experiments
- Use the Chaos Maturity Model to map the state of your chaos program, including realistic goals
Table of contents
- I. Introduction
- 1. Why Do Chaos Engineering?
- 2. Managing Complexity
- II. The Principles of Chaos
- 3. Hypothesize about Steady State
- 4. Vary Real-World Events
- 5. Run Experiments in Production
- 6. Automate Experiments to Run Continuously
- 7. Minimize Blast Radius
- III. Chaos In Practice
- 8. Designing Experiments
- 9. Chaos Maturity Model
- 10. Conclusion
- Title: Chaos Engineering
- Release date: August 2017
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781491953068
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