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Diagnose failed or unhealthy Dynamo deployments. Use when pods, model-cache jobs, PVCs, workers, frontend/router health, endpoints, or benchmark jobs fail; use recipe-runner/router-starter before this for normal bring-up.
$ npx -y skills add NVIDIA/skills --skill dynamo-troubleshoot --agent claude-codeHow it fires
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/dynamo-troubleshootContext preview
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Diagnose failed or unhealthy Dynamo deployments. Use when pods, model-cache jobs, PVCs, workers, frontend/router health, endpoints, or benchmark jobs fail; use recipe-runner/router-starter before this for normal bring-up.
name: dynamo-troubleshoot
description: Diagnose failed or unhealthy Dynamo deployments. Use when pods, model-cache jobs, PVCs, workers, frontend/router health, endpoints, or benchmark jobs fail; use recipe-runner/router-starter before this for normal bring-up.
license: Apache-2.0
metadata:
author: Dan Gil <dagil@nvidia.com>
tags:
- dynamo
- kubernetes
- troubleshooting
- day-2<!-- SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. SPDX-License-Identifier: CC-BY-4.0 -->
Turn a Dynamo failure into a clear problem class, strongest signal, and next action. Start with read-only evidence, avoid secrets, and fix one layer at a time.
Run:
python3 scripts/collect_dynamo_debug_bundle.py \
--namespace "${NAMESPACE}"If the user names a deployment, include it:
python3 scripts/collect_dynamo_debug_bundle.py \
--namespace "${NAMESPACE}" \
--deployment-name <deployment-name>Do not collect Kubernetes secrets. Do not print Hugging Face tokens.
Use `references/failure-decision-tree.md` and classify into one primary bucket:
Check in this order:
1. namespace, storage class, GPU nodes, and HF secret existence 2. PVC and model-download job 3. `DynamoGraphDeployment` status and events 4. pod status, `describe pod`, and container logs 5. frontend service and port-forward 6. `/v1/models` 7. `/v1/chat/completions` 8. benchmark job only after endpoint smoke test passes
Prefer the smallest reversible change:
After each fix, rerun the relevant readiness check before moving deeper.
| Script | Purpose | Arguments | |---|---|---| | `scripts/collect_dynamo_debug_bundle.py` | Collect a read-only debug bundle (pods, events, jobs, PVCs, CR status) | `--namespace`, `--deployment-name`, `--output-dir` |
Invoke via the agentskills.io `run_script()` protocol:
run_script("scripts/collect_dynamo_debug_bundle.py", args=["--namespace", "dynamo-demo"])Collect everything in a namespace for triage:
python3 scripts/collect_dynamo_debug_bundle.py --namespace dynamo-demo
Scope to a single failing deployment:
python3 scripts/collect_dynamo_debug_bundle.py \ --namespace dynamo-demo \ --deployment-name qwen-vllm-disagg
Equivalent through the agent protocol:
run_script("scripts/collect_dynamo_debug_bundle.py", args=["--namespace", "dynamo-demo", "--deployment-name", "qwen-vllm-disagg"])Return:
| Symptom | Likely cause | Next step | |---|---|---| | `kubectl` returns Forbidden on events/pods | Service account lacks read RBAC | Ask operator for read-only role binding on the namespace | | Bundle missing `DynamoGraphDeployment` status | Operator not installed or different namespace | Verify `dynamo-platform` operator is installed and watching the namespace | | Model-download job in `Pending` | PVC unbound or HF secret missing | Fix PVC binding or create the named HF secret, then rerun the job | | Worker pods `CrashLoopBackOff` | Image/runtime mismatch or GPU not available | Inspect container logs; check `nvidia.com/gpu` allocatable on nodes |
See `BENCHMARK.md` for the NVCARPS-EVAL performance report (auto-generated by the NVSkills CI pipeline). To refresh, re-run `/nvskills-ci` on an upstream PR touching this skill.
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