Chaos Experiments under the lens of AIOps

on YouTube ↗18m

" summary

MiniKube ecommerce demo with ~10–11 microservices uses Splunk Observability + an AIOps layer, litmuschaos to inject 4,000 ms network latency into the card service for 200s, and locust simulating 30 users (spawn rate 2). Splunk detects and alerts on latency and issues a prediction before the peak, a dashboard counts litmus-triggered pod launches, and a runbook can auto-remediate (rebuild/reset). Hypothesis that AIOps recognizes and responds to chaos experiments is proven by the live demo.

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" chapters (10)

1. 0:00AIOps and chaos engineering intro
2. 1:04AIOps vs chaos engineering
3. 3:09AIOps observe engage act model
4. 5:13Planning chaos experiments
5. 6:37Setting chaos hypothesis
6. 8:00Live demo environment
7. 10:25Injecting latency with Litmus Chaos
8. 13:18AIOps response to chaos
9. 16:30Detecting chaos via observability
10. 17:13Summary

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