Troubleshoot GKE TPU performance degradation with ML Diagnostics Workload Monitoring

Diagnose and mitigate Cloud TPU training throughput drops and step-time regressions (15%+ drop in TPU duty cycle) on Google Kubernetes Engine (GKE) by correlating ML Diagnostics Workload Monitoring MonitoredEvent analyzer reports with 1-minute Cloud Monitoring system metrics and GKE node topology labels.

Prerequisites