Kubernetes-Defined Monitoring [I]
summary
Demonstrates two concrete data-collection models: a sidecar per-pod exporter and a sysdig kernel tap/system-call capture that auto-correlates metrics with Kubernetes metadata; shows live demos (laptop cluster) of drilling from namespace → deployment → pod to inspect CPU, HTTP payloads, logs and save syscall traces. Implements annotations-as-monitoring-as-code that creates teams, dashboards and alerts automatically (examples: sustained 60s avg response >500ms across service, per-container CPU >80%), and the demos work end-to-end.
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chapters (9)
- 0:00Intro
- 1:25Agenda
- 2:22What is KubernetesDefined Monitoring
- 3:46How does this impact monitoring
- 5:18Getting the data
- 6:02Models
- 8:32Guidelines
- 15:24Troubleshooting
- 21:16Teams
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