Chaos Engineering for Cloud Native
summary
Covers running chaos experiments against Kubernetes clusters using ChaosNative and LitmusChaos, defining measurable SLOs, and tying failures to observability tools like Honeycomb to prove impact. Recommends concrete practices: progressive blast radius, automated CI experiments, concrete fault types (network, CPU, disk, pod kill), and validated steady-state hypothesis checks with runbooks and automated rollback policies. Shows example experiment flow, failure signals to monitor, and how to gate rollout if recovery fails.
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chapters (6)
- 0:00Introduction
- 1:44What is Chaos Engineering
- 7:00Preparing for failures
- 12:40Real-world experiments
- 17:07Benefits of chaos testing
- 21:14Conclusion and call to action
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