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Incident Response for GPU Fleets

GPU incident response restores useful service while preserving enough evidence to diagnose the failure. Mitigation, repair and return-to-service checks have different purposes.

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RELATED CONCEPTS

GPU Failure Modes and XID Errors Stragglers and Hangs Node Health Checks and Burn-In SLOs for AI Systems On-Call Narratives That Land Elastic and Fault-Tolerant Training

LESSONS THAT TEACH THIS

Inference EngineeringCapstone: investigate an SLO miss and write a usable runbook330 min→Fleet and ReliabilityDesign the repair queue and page for urgent unresolved impact30 min→

PRACTICE THIS IN REAL QUESTIONS

Behavioral & OwnershipWalk me through the worst on-call incident you have handled.→Kubernetes, Slurm & GPU SchedulingA GPU in a running 512-GPU training job is throwing errors. How do you get it out of the job without losing the run?→Napkin Math, Cost & CapacityHow long does that 70B run take on 16,384 H100s at 40% MFU?→Behavioral & OwnershipThree incidents are open, your pager is going off, and a customer is escalating. What do you do first?→GPU Fleet Reliability & ObservabilityYou own the on-call rota for a GPU fleet. What is allowed to wake someone at 3am, and what must not?→GPU Fleet Reliability & ObservabilityA node reports a GPU has fallen off the bus. What happened, what can software do, and what should the platform do automatically?→