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GPU Observability & Profiling

observabilityprofilinggputeam:mido/infra
Trial

Why?

  • Troubleshooting performance, utilization, and correctness of GPU workloads requires specialized telemetry and profiling tools.
  • Better observability unlocks higher utilization and faster issue resolution for training & inference.

What?

  • Adopt tooling for GPU telemetry and profiling (NVIDIA Nsight, DCGM, PyTorch/TensorBoard profilers, Prometheus exporters).
  • Establish logging and tracing practices that correlate GPU metrics with jobs, datasets, and deployments.
  • Build runbooks for common performance issues and capacity bottlenecks.