gke-ai-troubleshooting-handle-disruption-gpu-tpu skillA
gke-ai-troubleshooting-handle-disruption-gpu-tpu is agent-read markdown (skill) from gke-labs/kube-agents: Diagnoses, predicts, and mitigates node disruptions during Compute Engine host maintenance and hardware or software maintenance events for GPU and TPU workloads on GKE. Use when diagnosing node disruptions, predicting host maintenance events on GPU/TPU nodepools, inspecting node interruption PromQL metrics, auditing node taints, or configuring workload protection strategies (graceful termination, opportunistic maintenance, PodDisruptionBudgets). Don't use for general GKE cluster creation, networ.
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# Handle Disruption on GPUs and TPUs Troubleshooting
## 🔍 Diagnostic Workflow
### Step 0: Context Acquisition
- **Mandatory**: When a user asks to debug or investigate an actual workload
disruption, node crash, or unexpected restart without providing complete
cluster details, you MUST immediately halt and request all missing mandatory
parameters (`project_id`, `location`, `cluster_name`, `timestamp`) BEFORE
delivering theories or general diagnostic commands. Only skip context
acquisition if the user explicitly requests a generic reusable runbook or
provides a complete static telemetry/log dump for offline analysis.
- **Optional**: `node_name`, `workload_name`, `workload_namespace`,
`nodepool_name`.
### Step 1: [Low Risk] Check for Upcoming Scheduled Maintenance
- **Action**: Propose running `kubectl` to check if nodes have the scheduled
maintenance label indicating an upcoming disruption.
- **Example Command**:
```bash
kubectl get nodes -l cloud.google.com/scheduled-maintenance-time -L cloud.google.com/scheduled-maintenance-time
```
- **Interpretation**: The `SCHEDULED-MAINTENANCE-TIME` column shows the Unix
…Read the whole file at its exact version.
How to install
mdr add gke-labs/kube-agents/gke-ai-troubleshooting-handle-disruption-gpu-tpu@git:20260807.d47bdf1mdr add gke-labs/kube-agents/gke-ai-troubleshooting-handle-disruption-gpu-tpu@sha256:706f73fa33d18d53Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_bhonotsekjkziwwd)
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Versions
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (6505 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
gke-labs/kube-agents · 64 stars · license Apache-2.0 · pushed 2026-09-23 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_bhonotsekjkziwwd GET https://markdownregistry.com/api/v1/resolve?ref=gke-labs/kube-agents/gke-ai-troubleshooting-handle-disruption-gpu-tpu GET https://markdownregistry.com/api/v1/blob/706f73fa33d18d53f907851421078494912e613a485ee62d88d273696d3bc34f
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