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GPU Pod Readiness

BeaverDeck uses this check to identify a specific gpu condition that may need operator review.

Permissions: viewing checks requires insights: view. Opening a linked object or logs requires the corresponding resource permission, and the BeaverDeck ServiceAccount must be allowed to read the Kubernetes resources used by the check. Suppressing a finding requires insights: edit and affects all users.
Check typegpu-pod-unready
Insights sectionGPU Insights
Alert severityWarning

When It Reports A Finding

A GPU-requesting Pod is assigned to a node but remains not Ready for at least 10 minutes from its Ready-condition transition or creation time.

Why This Is A Problem

The Pod holds GPU allocation without serving work, which reduces usable capacity and can conceal driver, image, startup, or application failures.

Recommended Response

  1. Inspect waiting container reasons, events, current and previous logs, and readiness probes.
  2. Verify the GPU device plugin, runtime, drivers, mounted devices, and application startup.
  3. Repair the owning workload or node and confirm that the Pod becomes Ready or releases the allocation.

Scope And Limitations

Long model downloads, compilation, or deliberate warm-up can exceed ten minutes. Tune the workload and interpret the alert with expected startup behavior.

After remediation: refresh GPU Insights and verify the underlying resource or metric. Suppress the finding only when the condition is intentional and its risk is accepted.