~/talk

But Wait! There's...Still More‽ - Observability Data Volumes and Strategies for Managing Them

slides:none on file

Shows telemetry growth hitting terabytes to petabytes per month and names concrete pain points: storage, write/ingest costs, read/index costs, and ops expertise. Recommends specific mitigations: lower scrape/sample rates, downsampling, retention tiers, label aggregation, and dropping unused series, and cites tools: Prometheus ecosystems (Thanos, Cortex), Prometheus Mimir analyze CLI, OpenTelemetry Collector, Honeycomb/Refinery for tail sampling and Pixie/Pyroscope for profiling. Claims tracing/logs can explode costs and reports these approaches work in practice for lowering volume and cost.

AI-written summary · about

  1. 0:00Welcome
  2. 1:01Speaker overview
  3. 2:49Observability history
  4. 4:14Modern observability complexity
  5. 6:26Metrics and logs explosion
  6. 8:53Distributed tracing challenges
  7. 10:16Continuous profiling evolution
  8. 11:42Storage and cost implications
  9. 12:47Telemetry processing costs
  10. 14:13Querying observability data
  11. 15:36Operational challenges
  12. 16:19Flawed cost-cutting approaches
  13. 18:27Metric optimization
  14. 20:35Dropping unused metrics
  15. 22:01Log optimization
  16. 23:46Tracing optimization
  17. 25:52Profiling optimization
  18. 26:35Automated solutions
  19. 27:18Q&A
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