Lightning Talk: Think Like a Chaos Engineer: Simulating User Anomalies the Litmus Way
summary
Simulates common user failures by turning hypotheses into concrete LitmusChaos faults and observability checks: map a rapid login surge to pod-cpu-hog and pod-memory-hog, map bulk uploads to pod-disk-fill and pod-io-stress, and map high concurrency to network partition and container-kill faults; run experiments against the login/upload services, watch latency, error rates and alerts, verify autoscaling, cleanup or restart behavior, and use the Litmus SDK to generate custom experiments and pre/post checks.
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chapters (16)
- 0:00Chaos engineering intro
- 1:32Common user anomalies
- 3:16Rapid login problems
- 5:02Fault hypothesis for logins
- 7:48Memory testing in logins
- 9:57Bulk upload failures
- 11:41High IO from uploads
- 13:07Network partitions under load
- 13:51Container failure sim
- 14:55Custom chaos experiments
- 15:37Q&A: Benefits
- 18:27Q&A: Scripted vs unscripted
- 20:14Q&A: Starting experiments
- 22:05Q&A: Litmus contest
- 22:52Q&A: Custom Litmus tests
- 24:40Q&A: AI in chaos
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