GKE adds JobSet efficiency metrics in preview
Google Kubernetes Engine is now offering two new system metrics in preview to monitor the efficiency of GKE training JobSets. These metrics, kubernetes.io/jobset/scheduling_goodput and kubernetes.io/jobset/proxy_runtime_goodput, aim to provide insights into resource availability and accelerator productivity during training jobs. They are accessible via the GKE metrics and a dedicated JobSet monitoring dashboard.
Features (1) ›
- Google Kubernetes Engine
To monitor the efficiency of the GKE training JobSet, the following two GKE system metrics are available in Preview: kubernetes.io/jobset/scheduling_goodput : the fraction of time that all the resources required to run the training JobSet are available. kubernetes.io/jobset/proxy_runtime_goodput : the fraction of time that all required accelerators are productive. This metric provides an estimate of the real runtime goodput. For details about GKE metrics, see Kubernetes metrics . For details about goodput metrics that are used to measure efficiency, see Monitor goodput with the ML Goodput Meas
https://docs.cloud.google.com/release-notes#May_25_2026