operator_deployment.md

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# Deploying Dynamo Inference Graphs to Kubernetes using the Dynamo Cloud Platform

This guide walks you through deploying an inference graph created with the Dynamo SDK onto a Kubernetes cluster using the Dynamo cloud platform and the Dynamo deploy CLI. The Dynamo cloud platform provides a streamlined experience for deploying and managing your inference services.

## Prerequisites

Before proceeding with deployment, ensure you have:

- [Dynamo Python package](../../get_started.md#installation) installed
- A Kubernetes cluster with the [Dynamo cloud platform](dynamo_cloud.md) installed
- Ubuntu 24.04 as the base image for your services
- Required dependencies:
  - Helm package manager
  - Rust packages and toolchain

You must have first followed the instructions in [deploy/dynamo/helm/README.md](https://github.com/ai-dynamo/dynamo/blob/main/deploy/dynamo/cloud/helm/README.md) to install Dynamo Cloud on your Kubernetes cluster.

## Understanding the Deployment Process

The deployment process involves two main steps:

1. **Local Build (`dynamo build`)**
   - Creates a Dynamo service archive containing:
     - Service code and dependencies
     - Service configuration and metadata
     - Runtime requirements
     - Service graph definition
   - This archive is used as input for the remote build process

2. **Remote Image Build**
   - A `yatai-dynamonim-image-builder` pod is created in your cluster
   - This pod:
     - Takes the Dynamo service archive
     - Containerizes it using the specified base image
     - Pushes the final container image to your cluster's registry
   - The build process is managed by the Dynamo operator

## Deployment Steps

### 1. Configure Environment Variables

First, set up your environment variables for working with Dynamo Cloud. You have two options for accessing the `dynamo-store` service:

#### Option 1: Using Port-Forward (Local Development)
This is the simplest approach for local development and testing:

```bash
# Set your project root directory
export PROJECT_ROOT=$(pwd)

# Set your Kubernetes namespace (must match the namespace where Dynamo cloud is installed)
export KUBE_NS=hello-world

# In a separate terminal, run port-forward to expose the dynamo-store service locally
kubectl port-forward svc/dynamo-store 8080:80 -n $KUBE_NS

# Set DYNAMO_CLOUD to use the local port-forward endpoint
export DYNAMO_CLOUD=http://localhost:8080
```

#### Option 2: Using Ingress/VirtualService (Production)
For production environments, you should use proper ingress configuration:

```bash
# Set your project root directory
export PROJECT_ROOT=$(pwd)

# Set your Kubernetes namespace (must match the namespace where Dynamo cloud is installed)
export KUBE_NS=hello-world

# Set DYNAMO_CLOUD to your externally accessible endpoint
# This could be your Ingress hostname or VirtualService URL
export DYNAMO_CLOUD=https://dynamo-cloud.nvidia.com  # Replace with your actual endpoint
```

``` {note}
The `DYNAMO_CLOUD` environment variable is required for all Dynamo deployment commands. Make sure it's set before running any deployment operations.
```

### 2. Build the Dynamo Base Image

Before building your service, you need to ensure the base image is properly set up:

1. For detailed instructions on building and pushing the Dynamo base image, see the [Building the Dynamo Base Image](../../get_started.md#building-the-dynamo-base-image) section in the main README.

2. Export the image from the previous step to your environment.
```bash
# Export the image from the previous step to your environment
export DYNAMO_IMAGE=<your-registry>/<your-image-name>:<your-tag>

# Navigate to your project directory
cd $PROJECT_ROOT/examples/hello_world

# Build the service and capture the tag
DYNAMO_TAG=$(dynamo build hello_world:Frontend | grep "Successfully built" | awk '{ print $3 }' | sed 's/\.$//')
```

### 3. Deploy to Kubernetes

Deploy your service using the Dynamo deployment command:

```bash
# Set your Helm release name
export DEPLOYMENT_NAME=hello-world

# Create the deployment
dynamo deployment create $DYNAMO_TAG -n $DEPLOYMENT_NAME
```

#### Managing Deployments

Once you have deployments running, you can manage them using the following commands:

To see a list of all deployments in your namespace:

```bash
dynamo deployment list
```
This command displays a table of all deployments.

To get detailed information about a specific deployment:

```bash
dynamo deployment get $DEPLOYMENT_NAME
```

To update a specific deployment:

```bash
dynamo deployment update $DEPLOYMENT_NAME [--config-file FILENAME] [--env ENV_VAR]
```

To remove a deployment and all its associated resources:

```bash
dynamo deployment delete $DEPLOYMENT_NAME
```

```{warning}
This command permanently deletes the deployment and all associated resources. Make sure you have any necessary backups before proceeding.
```

### 4. Test the Deployment

The deployment process creates several pods:
1. A `yatai-dynamonim-image-builder` pod for building the container image
2. Service pods prefixed with `$DEPLOYMENT_NAME` once the build is complete

To test your deployment:

```bash
# Forward the service port to localhost
kubectl -n ${KUBE_NS} port-forward svc/${DEPLOYMENT_NAME}-frontend 3000:3000

# Test the API endpoint
curl -X 'POST' 'http://localhost:3000/generate' \
    -H 'accept: text/event-stream' \
    -H 'Content-Type: application/json' \
    -d '{"text": "test"}'
```

## Expected Output

When you send a request with "test" as input, you'll see how the text flows through each service:

```
Frontend: Middle: Backend: test-mid-back
```

This demonstrates the service pipeline:
1. The Frontend receives "test"
2. The Middle service adds "-mid" to create "test-mid"
3. The Backend service adds "-back" to create "test-mid-back"