ECS

Dynamo Deployment of vLLM Example on AWS ECS

1. EC2 Cluster Setup (for vLLM workloads)

1. Go to AWS ECS console, Clusters tab and click on Create cluster with name dynamo-GPU
2. Input the cluster name and choose AWS EC2 instances as the infrastructure. This option will create a cluster with EC2 instances to deploy containers.
3. Choose the ECS-optimized GPU AMI Amazon Linux 2 (GPU) (Amazon ECS–optimized), which includes NVIDIA drivers and the Docker GPU runtime out of the box.
4. Choose g6e.2xlarge as the EC2 instance type and add an SSH Key pair so you can log in the instance for debugging purpose. To test with disaggregated serving, we need at least 2 GPUs, so you can choose g6e.12xlarge with 4 GPUs
5. Set Root EBS volume size as 200
6. For the networking, use the default settings. Make sure the security group has

• an inbound rule which allows "All traffic" from this security group.
• an inbound rule for port 22 and 8000, so that you can ssh into the instance for debugging purpose

7. Select Turn on for Auto-assign public IP option.
8. Click on Create and a cluster will be deployed through cloudformation.

2. Fargate Cluster Setup (for ETCD/NATS services)

1. Go to AWS ECS console, Clusters tab and click on Create cluster
2. Input the cluster name as dynamo-fargate
3. Choose AWS Fargate (serverless) as the infrastructure
4. For networking, use the same VPC and subnets as the EC2 cluster to ensure connectivity between services
5. For the security group, use the same security group as the EC2 cluster. This automatically allows communication between all services.
6. Ensure outbound rules allow all traffic (default setting) so the Fargate tasks can download container images and communicate externally
7. Click on Create to deploy the Fargate cluster

3. ETCD/NATS Task Definitions Setup

Add a task for ETCD and NATS services to run on Fargate. A sample task definition JSON is attached.

3.1 Create the ecsTaskExecutionRole (Required)

Before creating the task definitions, you need to create the ecsTaskExecutionRole IAM role. This role allows ECS to pull container images from registries and write logs to CloudWatch on your behalf.

Important

If you create task definitions through the AWS Console's step-by-step wizard, this role is created automatically. However, when importing task definitions from JSON (as recommended in this guide), you must create this role manually.

Follow the AWS documentation on creating the task execution IAM role to create a role named ecsTaskExecutionRole with the AmazonECSTaskExecutionRolePolicy policy attached.

Based on the task definition, you may need to add Amazon CloudWatch permissions and AWS Secrets Manager permissions to the ecsTaskExecutionRole. See details in the Amazon CloudWatch Logs permissions reference the AWS Secrets Manager authentication and access control guide

Note

The role ARN will be arn:aws:iam::<your-account-id>:role/ecsTaskExecutionRole. Make sure to update <your-account-id> in any task definition JSON files with your actual AWS account ID.

3.2 Task Definition Configuration

1. ETCD container

• Container name use etcd
• Image URL is bitnamilegacy/etcd and Yes for Essential container
• Container port

Container port	Protocol	Port name	App protocol
2379	TCP	2379	HTTP
2380	TCP	2380	HTTP

• Environment variable key is ALLOW_NONE_AUTHENTICATION and value is YES

2. NATS container

• Container name use nats
• Image URL is nats and Yes for Essential container
• Container port

Container port	Protocol	Port name	App protocol
4222	TCP	4222	HTTP
6222	TCP	6222	HTTP
8222	TCP	8222	HTTP

• Docker configuration, add -js, --trace in Command

4. vLLM Task Definitions Setup

Note

Ensure you have created the ecsTaskExecutionRole as described in section 3.1 before creating these task definitions.

1. Dynamo vLLM Frontend and Decoding Worker Task This task will create vLLM frontend, processors, routers and a decoding worker. Please follow steps below to create this task

• Set container name as dynamo-frontend and use prebuild Dynamo container.
• Choose Amazon EC2 instances as the Launch type with Task size 2 vCPU and 40 GBmemory
• Choose host as the Network mode.
• Container name use dynamo-vLLM-frontend
• Add your Image URL (You can use the prebuild Dynamo container) and Yes for Essential container. It can be AWS ECR URL or Nvidia NGC URL. If using NGC URL, please also choose Private registry authentication and add your Secret Manager ARN or name.
• Container port

Container port	Protocol	Port name	App protocol
8000	TCP	8000	HTTP

• Use 1 GPU for Resource allocation limits
• Environment variables settings as below. Will override the IP_ADDRESS later.

Key	Value type	Value
ETCD_ENDPOINTS	Value	http://IP_ADDRESS:2379
NATS_SERVER	Value	nats://IP_ADDRESS:4222

• Docker configuration Add sh,-c in Entry point and cd examples/backends/vllm && python -m dynamo.frontend --router-mode kv & python3 -m dynamo.vllm --model Qwen/Qwen3-0.6B --enforce-eager in Command

2. Dynamo vLLM PrefillWorker Task Create the PrefillWorker task same as the frontend worker, except for following changes

• Set container name as dynamo-prefill
• No container port mapping
• Docker configuration with command cd examples/backends/vllm && python3 -m dynamo.vllm --model Qwen/Qwen3-0.6B --enforce-eager --is-prefill-worker

5. Task Deployment

You can create a service or directly run the task from the task definition

1. ETCD/NATS Task

• Choose the Fargate cluster (dynamo-fargate) for Existing cluster created in step 2.
• Select Launch type as FARGATE
• In the Networking section, select the same VPC and subnets used for the EC2 cluster
• For Security group, select the same security group used by the EC2 cluster
• Verify that outbound rules allow all traffic for downloading images and external communication
• Wait for this deployment to finish, and get the Private IP of this task.

2. Dynamo Frontend and Decoding Worker Task

• Choose the EC2 cluster (dynamo-GPU) for Existing cluster created in step 1.
• In the Container Overrides, use the IP for ETCD/NATS task for the ETCD_ENDPOINTS and NATS_SERVER values.
• After the deployment, an aggregated serving endpoint is created and you can test it with scripts in step 6.

3. Dynamo PrefillWorker Task

• For disaggregated serving, you can deploy a separate prefill worker on another GPU. Choose the EC2 cluster (dynamo-GPU) for Existing cluster created in step 1 with at least 2 GPUs ( g6e.12xlarge for example)
• In the Container Overrides, use the IP for ETCD/NATS task for the ETCD_ENDPOINTS and NATS_SERVER values.

6. Testing

Find the public IP of the dynamo frontend task from the task page. Run following commands to query the endpoint.

export DYNAMO_IP_ADDRESS=TASK_PUBLIC_IP_ADDRESS
curl http://$DYNAMO_IP_ADDRESS:8000/v1/models
curl http://$DYNAMO_IP_ADDRESS: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
  }'

You should be able to see the responses from the hosted endpoint.