How Chaos Engineering Ensures the Resilience of Your Services
summary
Explains how chaos engineering helps make distributed services resilient by defining hypotheses about a stable version, running controlled experiments (including automated experiments) in production, and limiting failure blast radius. Demonstrations use a Kubernetes cluster to show building hypotheses, executing experiments, automating them, and minimizing failure propagation.
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chapters (21)
- 0:00Introduction
- 1:12What is Chaos Engineering
- 3:43Why failures happen
- 5:04Where to inject chaos
- 7:18Start with small tests
- 8:00Chaos Engineering phases
- 10:06Steady state and metrics
- 12:35Defining correct metrics
- 14:23Health checks vs metrics
- 17:13Hypothesis phase
- 19:18Designing experiments
- 20:25Safe production testing
- 21:50Collecting results and learnings
- 22:57Correction phase
- 24:00Tool demonstration
- 25:06Governance and resilience
- 26:31Chaos tools
- 29:03Chaos Monkey and Chaos Gorilla
- 31:15Chaos Mesh in action
- 38:59Summary and insights
- 39:19Q&A
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