Dynamo Troubleshoot

SkillCloud & infra

Lets your agent diagnose failed or unhealthy Dynamo deployments, like broken pods, workers, or endpoints.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Dynamo Troubleshoot skill

About this capability

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.

What this skill tells your AI

The instructions your AI receives, as published by nvidia/skills in skills/dynamo-troubleshoot/SKILL.md and read by ahel’s review.

Purpose

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.

Prerequisites

  • Python 3.10+ on the operator machine.
  • kubectl configured with read access to the target namespace.
  • Permission to read pods, events, jobs, PVCs, and DynamoGraphDeployment resources (NOT secrets).
  • Network reachability to the cluster API server.

Instructions

1. Collect A Read-Only Bundle

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.

2. Classify The Failure

Use references/failure-decision-tree.md and classify into one primary bucket:

  • cluster/platform
  • namespace/secret
  • model cache/PVC/download
  • image pull/runtime image
  • GPU scheduling/resources
  • operator/DynamoGraphDeployment reconciliation
  • frontend/router
  • worker/backend
  • endpoint/API
  • benchmark/perf job

3. Debug Top Down

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

4. Fix One Layer At A Time

Prefer the smallest reversible change:

  • create missing namespace or HF secret
  • patch storageClassName
  • patch image tag or image pull secret
  • reduce GPU request only if the recipe can still be valid
  • switch KV router to approximate mode only if workers do not publish events
  • restart failed jobs after fixing the underlying config

After each fix, rerun the relevant readiness check before moving deeper.

Available Scripts

ScriptPurposeArguments
scripts/collect_dynamo_debug_bundle.pyCollect 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"])

Examples

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"])

Output Contract

Return:

  • problem class
  • evidence checked
  • strongest signal
  • likely cause
  • exact next command or patch
  • what was ruled out
  • whether it is safe to continue deployment or benchmarking

Limitations

  • Read-only. Never mutates the cluster; remediation commands are returned, not executed.
  • Will not collect secrets or print Hugging Face tokens; some failure modes (auth) may need user-side inspection.
  • Bundle size grows with deployment size; on very large namespaces, scope with --deployment-name.
  • Does not validate disagg transport — use dynamo-interconnect-check for that.

Troubleshooting

SymptomLikely causeNext step
kubectl returns Forbidden on events/podsService account lacks read RBACAsk operator for read-only role binding on the namespace
Bundle missing DynamoGraphDeployment statusOperator not installed or different namespaceVerify dynamo-platform operator is installed and watching the namespace
Model-download job in PendingPVC unbound or HF secret missingFix PVC binding or create the named HF secret, then rerun the job
Worker pods CrashLoopBackOffImage/runtime mismatch or GPU not availableInspect container logs; check nvidia.com/gpu allocatable on nodes

Benchmark

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.

References

  • Read references/failure-decision-tree.md for bucket-specific checks.
  • Use scripts/collect_dynamo_debug_bundle.py for read-only bundle collection.

Signals

GitHub stars
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Forks
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Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
dynamo-troubleshoot
Source
github.com/nvidia/skills