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ClickHouse stores high-volume telemetry data.

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Talks To

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How It Fits

ClickHouse is the analytical datastore behind the telemetry experience. Ingester writes normalized telemetry into ClickHouse, and Apiserver queries it when users inspect metrics, traces, logs, profiles, Kubernetes state, and related views. The database is deliberately separate from PostgreSQL because telemetry has a different access pattern from configuration metadata. It receives high-volume writes, retains time-series and event-style data, and serves analytical queries over that data.

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Stores

  • Metrics
  • Traces
  • Logs
  • Profiling data
  • Kubernetes state and resource history

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Operational Notes

ClickHouse capacity has the largest effect on telemetry query performance, ingestion throughput, and storage footprint. Operators should think about it as both a write target and a query engine: ingestion pressure, expensive queries, retention, and disk growth all meet here. If the deployment uses bundled ClickHouse, the chart uses the Altinity ClickHouse Operator to create and manage the ClickHouse cluster and related services. If the deployment uses external ClickHouse, the same runtime relationship remains: Ingester needs to write successfully, and Apiserver needs to query successfully.