GKE

Dynamo Deployment on GKE

Pre-requisites

Install gcloud CLI

https://cloud.google.com/sdk/docs/install

Create GKE cluster

export PROJECT_ID=<>
export REGION=<>
export ZONE=<>
export CLUSTER_NAME=<>
export CLUSTER_MACHINE_TYPE=n2-standard-4
export NODE_POOL_MACHINE_TYPE=g2-standard-24
export GPU_TYPE=nvidia-l4
export GPU_COUNT=2
export CPU_NODE=2
export GPU_NODE=2
export DISK_SIZE=200

gcloud container clusters create ${CLUSTER_NAME} \
 	--project=${PROJECT_ID} \
 	--location=${ZONE} \
	--subnetwork=default \
    --disk-size=${DISK_SIZE} \
	--machine-type=${CLUSTER_MACHINE_TYPE} \
 	--num-nodes=${CPU_NODE}

Create GPU pool

gcloud container node-pools create gpu-pool \
 	--accelerator type=${GPU_TYPE},count=${GPU_COUNT},gpu-driver-version=latest \
 	--project=${PROJECT_ID} \
 	--location=${ZONE} \
 	--cluster=${CLUSTER_NAME} \
	--machine-type=${NODE_POOL_MACHINE_TYPE} \
    --disk-size=${DISK_SIZE} \
    --num-nodes=${GPU_NODE} \
    --enable-autoscaling \
    --min-nodes=1 \
    --max-nodes=3

Clone Dynamo GitHub repository

Note: Please make sure GitHub branch/commit version matches with Dynamo platform and VLLM container.

git clone https://github.com/ai-dynamo/dynamo.git

# Checkout to the desired branch
git checkout release/0.6.0

Set environment variables for GKE

export NAMESPACE=dynamo-system
kubectl create namespace $NAMESPACE
kubectl config set-context --current --namespace=$NAMESPACE

export HF_TOKEN=<HF_TOKEN>
kubectl create secret generic hf-token-secret \
  --from-literal=HF_TOKEN=${HF_TOKEN} \
  -n ${NAMESPACE}

Install Dynamo Kubernetes Platform

See installation steps

After installation, verify the installation:

Expected output

kubectl get pods
NAME                                                              READY   STATUS             RESTARTS   AGE
dynamo-platform-dynamo-operator-controller-manager-69b9794fpgv9   2/2     Running            0          4m27s
dynamo-platform-etcd-0                                            1/1     Running            0          4m27s
dynamo-platform-nats-0                                            2/2     Running            0          4m27s

Deploy Inference Graph

We will deploy a LLM model to the Dynamo platform. Here we use Qwen/Qwen3-0.6B model with VLLM and disaggregated deployment as an example.

In the deployment yaml file, some adjustments have to/ could be made:

• (Required) Add args to change LD_LIBRARY_PATH and PATH of decoder container, to enable GKE find the correct GPU driver
• Change VLLM image to the desired one on NGC
• Add namespace to metadata
• Adjust GPU/CPU request and limits
• Change model to deploy

More configurations please refer to https://github.com/ai-dynamo/dynamo/tree/main/examples/deployments/GKE/vllm

Highlighted configurations in yaml file

Please note that LD_LIBRARY_PATH needs to be set properly in GKE as per Run GPUs in GKE

The following snippet needs to be present in the args field of the deployment yaml file:

export LD_LIBRARY_PATH=/usr/local/nvidia/lib64:$LD_LIBRARY_PATH
export PATH=$PATH:/usr/local/nvidia/bin:/usr/local/nvidia/lib64
/sbin/ldconfig

For example, refer to the following from examples/deployments/GKE/vllm/disagg_gke.yaml

metadata:
  name: vllm-disagg
  namespace: dynamo-system
spec:
  services:
    Frontend:
          image: nvcr.io/nvidia/ai-dynamo/vllm-runtime:0.6.0
    VllmDecodeWorker:
​​      resources:
        limits:
          gpu: "3"
          image: nvcr.io/nvidia/ai-dynamo/vllm-runtime:0.6.0
          args:
            - |
            export LD_LIBRARY_PATH=/usr/local/nvidia/lib64:$LD_LIBRARY_PATH
            export PATH=$PATH:/usr/local/nvidia/bin:/usr/local/nvidia/lib64
            /sbin/ldconfig
            python3 -m dynamo.vllm --model Qwen/Qwen3-0.6B

Deploy the model

cd dynamo/examples/deployments/GKE/vllm

kubectl apply -f disagg_gke.yaml -n ${NAMESPACE}

Expected output after successful deployment

kubectl get pods
NAME                                                              READY   STATUS    RESTARTS   AGE
dynamo-platform-dynamo-operator-controller-manager-c665684ssqkx   2/2     Running   0          65m
dynamo-platform-etcd-0                                            1/1     Running   0          65m
dynamo-platform-nats-0                                            2/2     Running   0          65m
vllm-disagg-frontend-5954ddc4dd-4w2cb                             1/1     Running   0          11m
vllm-disagg-vllmdecodeworker-77844cfcff-ddn4v                     1/1     Running   0          11m
vllm-disagg-vllmprefillworker-55d5b74b4f-zrskh                    1/1     Running   0          11m

Test the Deployment

export DEPLOYMENT_NAME=vllm-disagg

# Find the frontend pod
export FRONTEND_POD=$(kubectl get pods -n ${NAMESPACE} | grep "${DEPLOYMENT_NAME}-frontend" | sort -k1 | tail -n1 | awk '{print $1}')

# Forward the pod's port to localhost
kubectl port-forward deployment/vllm-disagg-frontend  8000:8000 -n ${NAMESPACE}

# disagg
curl localhost:8000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "Qwen/Qwen3-0.6B",
    "messages": [
    {
        "role": "user",
        "content": "In the heart of Eldoria, an ancient land of boundless magic and mysterious creatures, lies the long-forgotten city of Aeloria. Once a beacon of knowledge and power, Aeloria was buried beneath the shifting sands of time, lost to the world for centuries. You are an intrepid explorer, known for your unparalleled curiosity and courage, who has stumbled upon an ancient map hinting at ests that Aeloria holds a secret so profound that it has the potential to reshape the very fabric of reality. Your journey will take you through treacherous deserts, enchanted forests, and across perilous mountain ranges. Your Task: Character Background: Develop a detailed background for your character. Describe their motivations for seeking out Aeloria, their skills and weaknesses, and any personal connections to the ancient city or its legends. Are they driven by a quest for knowledge, a search for lost familt clue is hidden."
    }
    ],
    "stream":false,
    "max_tokens": 30
  }'

Response

{"id":"chatcmpl-bd0670d9-0342-4eea-97c1-99b69f1f931f","choices":[{"index":0,"message":{"content":"Okay, here’s a detailed character background for your intrepid explorer, tailored to fit the premise of Aeloria, with a focus on a","refusal":null,"tool_calls":null,"role":"assistant","function_call":null,"audio":null},"finish_reason":"stop","logprobs":null}],"created":1756336263,"model":"Qwen/Qwen3-0.6B","service_tier":null,"system_fingerprint":null,"object":"chat.completion","usage":{"prompt_tokens":190,"completion_tokens":29,"total_tokens":219,"prompt_tokens_details":null,"completion_tokens_details":null}}