What problem does it solve?
Slurm clusters on Amazon SageMaker HyperPod can fail in opaque ways: nodes stuck in down or drain states, jobs pending despite idle nodes, jobs stuck in COMPLETING after node replacement, or auto-recovery requests that silently never trigger. This Skill performs read-only diagnostics to classify the exact failure mode and point you to the authoritative AWS or Slurm documentation for remediation.
Core Features & Use Cases
- Automated cluster diagnostics: Runs a read-only script over SSM that checks node states, slurmctld health, slurmdbd connectivity, slurm.conf freshness, and stuck job queues.
- Symptom-to-doc decision table: Maps findings like "Node unexpectedly rebooted", GRES count mismatches, and Action:Reboot/Replace reason-string mismatches to the correct AWS and Slurm documentation sections.
- Auto-resume investigation: Explains why HyperPod --auto-resume did not restart a job, covering HMA flagging, NodeRecovery settings, and AMI version requirements.
- Use Case: A training job is stuck PENDING with REASON=Resources while sinfo shows idle nodes. Invoke this Skill with the cluster name and region; it confirms the orchestrator type, runs the diagnostic script, and links you to the controller-state recovery documentation.
Quick Start
Ask the assistant to diagnose why Slurm nodes are down or jobs are stuck on your HyperPod cluster, providing the cluster name and AWS region.