Incident Library
Applied filters Root causeHardware failureOrganisationIBMClear allEvery case under the filters, with no sentence; newest first.
Suggested filters Search, and the values found in your words appear here.

Graph

  • Root cause
  • Component
  • Symptom
  • Contributing factor
  • Case

Cases1 case

1 to 1 of 1

  1. Symptoms

    A Granite-20B training job running on 768 GPUs on IBM's Vela AI cluster suddenly showed a step time almost 3 times longer than before.

    Trigger

    A power card issue in one of the job's 96 nodes made the node throttle its GPUs from about 400W to roughly 150W.

    Root cause
    Component
    Contributing factor
    –
    Detection

    The team noticed the sudden rise in step time and debugged all 96 nodes of the job to find the node with the power card issue.

    Remediation
    • Debugged all 96 nodes of the job and found the node with the power card issue
    Action items
    • Add alerts at the infrastructure layer based on host VM logs, application logs and host BMC logs to find problem nodes quickly
    • Flag nodes with an active power break slowdown from nvidia-smi GPU counters in Autopilot and the Grafana dashboard
    Lessons

    In distributed training, a drop in the performance of a single node reduces the performance of the whole job until the slow node is identified and removed or fixed and the job restarts on healthy nodes. Alerts and health checks that locate such nodes let site reliability engineers tell users about infrastructure problems before the users notice them, and cut the time to find the root cause by over 2x.

Check your cluster for this

This case involves Server power supply and power capping. 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.

By root cause1