Software Development
GKE AI Troubleshooting TPU Metrics Monitoring
Monitors and troubleshoots GKE TPU workloads, nodes, and node pools using GKE system metrics and PromQL. Use when monitoring TensorCore duty cycle, TPU memory, node readiness, multi-host TPU node pool availability, host maintenance or preemption interruptions, and calculating MTTR or MTBI metrics for GKE TPUs. Don't use for general non-TPU GKE workload monitoring or non-metric TPU debugging.
- Publisher / source
- Google Skills (Verified)
- Upstream record
- google/skills
- Version
- Version 4
- Published
- Publication review
- Approved for publication
- Content fingerprint
976606f04633b0aef7a7741b5ae9b1f2d11af7c456d10dd9413fd95cb820839d