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chore: fix whitespace issues
Signed-off-by: Neal Vaidya <nealv@nvidia.com>
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examples/deployments/ECS/README.md

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# Dynamo Deployment of vLLM Example on AWS ECS
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## 1. ECS Cluster Setup
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## 1. ECS Cluster Setup
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1. Go to AWS ECS console, **Clusters** tab and click on **Create cluster** with name `dynamo-GPU`
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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.
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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.
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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.
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5. Set **Root EBS volume size** as `200`
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6. For the networking, use the default settings. Make sure the **security group** has
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- an inbound rule which allows "All traffic" from this security group.
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6. For the networking, use the default settings. Make sure the **security group** has
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- an inbound rule which allows "All traffic" from this security group.
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- an inbound rule for port 22 and 8000, so that you can ssh into the instance for debugging purpose
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7. Select `Turn on` for **Auto-assign public IP** option.
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8. Click on **Create** and a cluster will be deployed through cloudformation.
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1. ETCD container
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- Container name use `etcd`
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- Image URL is `bitnami/etcd` and **Yes** for Essential container
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- Container port
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- Container port
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|Container port|Protocol|Port name| App protocol|
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|-|-|-|-|
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2. NATS container
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- Container name use `nats`
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- Image URL is `nats` and **Yes** for Essential container
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- Container port
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- Container port
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|Container port|Protocol|Port name| App protocol|
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|-|-|-|-|
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Please follow steps below to create this task
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- Set container name as `dynamo-frontend` and use prebuild [Dynamo container](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-dynamo/containers/vllm-runtime).
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- Choose `Amazon EC2 instances` as the **Launch type** with **Task size** `2 vCPU` and `40 GB`memory
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- Choose `host` as the Network mode.
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- Choose `host` as the Network mode.
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- Container name use `dynamo-vLLM-frontend`
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- Add your Image URL (You can use the prebuild [Dynamo container](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-dynamo/containers/vllm-runtime)) 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.
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- Container port
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- Add your Image URL (You can use the prebuild [Dynamo container](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-dynamo/containers/vllm-runtime)) 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.
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- Container port
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|Container port|Protocol|Port name| App protocol|
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|-|-|-|-|
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|-|-|-|
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|ETCD_ENDPOINTS|Value|http://IP_ADDRESS:2379|
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|NATS_SERVER|Value|nats://IP_ADDRESS:4222|
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- Docker configuration
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- Docker configuration
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Add `sh,-c` in **Entry point** and `cd components/backends/vllm && python -m dynamo.frontend --router-mode kv & python3 -m dynamo.vllm --model Qwen/Qwen3-0.6B --enforce-eager` in **Command**
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2. Dynamo vLLM PrefillWorker Task
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You can create a service or directly run the task from the task definition
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1. ETCD/NATS Task
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- Choose the Fargate cluster for **Existing cluster** created in the hello world example.
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- Wait for this deployment to finish, and get the **Private IP** of this task.
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- Wait for this deployment to finish, and get the **Private IP** of this task.
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2. Dynamo Frontend Task
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- Choose the EC2 cluster for **Existing cluster** created in step 1.
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- In the **Container Overrides**, use the IP for ETCD/NATS task for the `ETCD_ENDPOINTS` and `NATS_SERVER` values.

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