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Cases2 cases

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  1. Symptoms

    At 12:32 Prometheus on the Cloud Platform was not available after a planned change, and the Prometheus pod had restarted several times. The platform lost its monitoring and had missing metrics for the period.

    Trigger

    A planned change restarted Prometheus at a time when the WAL count was high.

    Root cause
    Component
    Contributing factor
    Detection

    The team saw that the Prometheus pod had restarted several times after the planned change.

    Remediation
    • raised the Prometheus startupProbe threshold to 30 minutes
    Action items
    • Perform planned Prometheus restarts when the WAL count is lower
    • Set the default CPU and memory requests to meet maximum usage
    • Create a test setup that recreates the live WAL count
    • Explore the memory-snapshot-on-shutdown and auto-gomaxprocs feature flags
    • Explore storing WAL files remotely in a different location
    • Look into a blue-green Prometheus to test changes on a live-like setup before applying them to live
    • Spike into Amazon Managed Prometheus
  2. Symptoms

    Request latency from the Temporal Server History service, the service that starts workflow executions and records their progress, was higher and less steady than it should be on a self-hosted Kubernetes deployment. The CPU dashboard showed the history pods using less than 60 percent of their CPU, yet the same pods were being throttled.

    Trigger

    Normal load on History pods that had a CPU limit of 2 cores on 8-core nodes, with the Go runtime's GOMAXPROCS left at its default of one per node core.

    Root cause
    Component
    Contributing factor
    Detection

    A Prometheus query for CPU throttling showed the history pods throttled although their CPU usage read under 60 percent.

    Remediation
    • set the GOMAXPROCS environment variable to 2 to match the 2-core CPU limit
    Action items
    • Set GOMAXPROCS automatically from the Kubernetes CPU limit, from Temporal release 1.21.0
    Lessons

    A CPU usage graph averaged over 15 seconds or more can sit far below 100 percent while a container is being throttled, so throttling needs its own metric. A Go program in a container should have GOMAXPROCS matched to its CPU limit, or to its CPU request when it has no limit. The author recommends not using CPU limits at all.

Check your cluster for this

These 2 cases involve Prometheus and Container CPU limit. kubegap audits a Kubernetes cluster for gaps like these, read-only, from Claude Code or Codex; its checks cite public reports like the ones in this library.

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