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/dynamo-recipe-runner

@efd358a
by NVIDIA Corporationnvidia/skills3.5k stars
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Select, validate, patch, and deploy existing NVIDIA Dynamo Kubernetes recipes. Use for model/backend/GPU/deployment-mode recipe bring-up; use router-starter for router-only mode work and troubleshoot for broken deployments.

Use this Skill: https://skilld.dev/gh/nvidia/skills/dynamo-recipe-runner

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referencesk8s-recipe-workflow.md

≈726 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Kubernetes Recipe Workflow

<!-- SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. SPDX-License-Identifier: CC-BY-4.0 -->

Selection Rules

Use this order when multiple recipes match:

  1. exact model, framework, deployment mode, and GPU type/count
  2. exact model and framework, nearest deployment mode
  3. same framework and topology with a similar model size
  4. stop and ask before adapting an unrelated recipe

Treat recipes marked functional or experimental in recipes/README.md as usable for bring-up but do not claim production performance unless the recipe includes benchmark results.

Common Commands

Set the namespace:

export NAMESPACE=dynamo-demo
kubectl create namespace "${NAMESPACE}" --dry-run=client -o yaml | kubectl apply -f -

Create the Hugging Face secret without printing the token:

kubectl create secret generic hf-token-secret \
  --from-literal=HF_TOKEN="${HF_TOKEN}" \
  -n "${NAMESPACE}" \
  --dry-run=client -o yaml | kubectl apply -f -

Find storage classes:

kubectl get storageclass

Apply model cache:

kubectl apply -f recipes/<model>/model-cache/ -n "${NAMESPACE}"
kubectl logs -f job/model-download -n "${NAMESPACE}"
kubectl wait --for=condition=Complete job/model-download -n "${NAMESPACE}" --timeout=6000s

Apply deployment:

kubectl apply -f recipes/<model>/<framework>/<mode>/deploy.yaml -n "${NAMESPACE}"
kubectl get dynamographdeployment -n "${NAMESPACE}"
kubectl get pods -n "${NAMESPACE}" -o wide

Find frontend service:

kubectl get svc -n "${NAMESPACE}" | grep frontend

Smoke test:

kubectl port-forward svc/<frontend-service> 8000:8000 -n "${NAMESPACE}"
curl http://127.0.0.1:8000/v1/models

Readiness Signals

Healthy path:

  • model-download job completed
  • model cache PVC is bound
  • DynamoGraphDeployment exists and is not reporting reconciliation errors
  • frontend and worker pods are Running
  • containers are ready
  • frontend service exists
  • /v1/models returns at least one model
  • /v1/chat/completions returns a completion

Do not move to benchmarking until the smoke test passes.

Common Blockers

Storage:

  • storageClassName does not exist
  • PVC is pending
  • model cache path is not mounted in worker

Auth:

  • HF secret missing
  • secret key name does not match manifest env var
  • model license/access not accepted upstream

Images:

  • image tag still uses a placeholder
  • private registry pull secret missing
  • backend image does not include required backend/runtime version

Scheduling:

  • requested GPU count exceeds available nodes
  • wrong GPU SKU for recipe
  • node taints/tolerations missing

Routing:

  • frontend has DYN_ROUTER_MODE=kv but workers are not ready
  • KV events are expected but backend is not publishing them
  • service forwards to frontend but no workers are registered

Source: SKILL.md on GitHub

1 warning3mo3 checks · Risk SAFE
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    The skill facilitates the deployment of AI model recipes on Kubernetes using kubectl and a custom validation tool. It follows security best practices for secret management and includes a cryptographic signature to ensure the integrity of its files. No malicious patterns or high-risk vulnerabilities were detected.

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  • Snyk3mo

    Risk: MEDIUM · 1 issue

Signed by skilld at efd358a. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub yesterday.

Activeupdated 4 months ago
Other metadata
metadata
{
  "author": "Dan Gil <dagil@nvidia.com>",
  "tags": [
    "dynamo",
    "kubernetes",
    "recipes",
    "bring-up"
  ],
  "permissions": [
    "file_read",
    "network",
    "kubectl_exec"
  ]
}

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