---
title: Gke Tpu Metrics Monitoring — Invoked Exchange skill
description: 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.
doc_version: "1.0"
last_updated: "2026-08-03T08:16:41.280Z"
canonical: https://invoked.ai/skills/gke-tpu-metrics-monitoring
---

# Gke 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.

- Shared by: google/skills
- Composes surfaces: 
- Tool chain: 
- Add to Invoked: https://invoked.ai/skills/gke-tpu-metrics-monitoring

## Community usage

_Building — published once enough workspaces have run this skill._

## Sitemap

See the full [Exchange sitemap](https://invoked.ai/sitemap.md).