What It Does
Gke Ai Troubleshooting Tpu Metrics Monitoring packages a focused devops & cloud workflow for an AI agent. 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. It is best suited to users who can review the resulting actions and provide only the accounts, files, or command access needed for the task. It is not a substitute for human approval on destructive, financial, security-sensitive, or public-facing actions.
Popular Use Cases
- Inspect deployment or infrastructure state
- Automate a repeatable operations task
- Troubleshoot configuration and runtime issues
- Apply documented production practices
Install this Agent Skill
Claude Code
npx skills add https://github.com/google/skills --skill gke-ai-troubleshooting-tpu-metrics-monitoringCommands derived from the public GitHub SKILL.md record. Checked 2026-09-18. Review the source before running them.
Requirements
| Claude Code | Required / review |
| Codex | Required / review |
| Public SKILL.md source | Required / review |
| Review instructions and requested permissions before installation | Required / review |
| Paid service | Check source |
| Supported system | Check source |
Why It’s Popular
Gke Ai Troubleshooting Tpu Metrics Monitoring is a verified Agent Skill from google with a public SKILL.md, compatible with Claude Code, Codex, Gemini CLI.
