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Observability Pipeline

Kubernetes observability pipeline architecture

Intent​

Collect signals from workloads and cluster components, standardize labels, store by access pattern, and expose operations views tied to SLOs.

Key decisions​

  • Metrics are optimized for alerting and dashboards.
  • Logs carry enough context for forensic debugging without uncontrolled cardinality.
  • Traces show request path and dependency latency.
  • Events explain Kubernetes scheduling, lifecycle, and policy outcomes.

Review signals​

  • Every alert has an owner and an action.
  • Dashboards start from user impact.
  • LLM routes expose TTFT, tokens/sec, queue wait, and GPU pressure.
  • Storage retention matches incident and audit requirements.