AWS CDK Fargate Deployment Example

Introduction

This is a TypeScript-based CDK (Cloud Development Kit) example that demonstrates how to deploy a Python application to AWS Fargate. The example deploys a weather forecaster application that runs as a containerized service in AWS Fargate with an Application Load Balancer. The application is built with FastAPI and provides two weather endpoints:

/weather - A standard endpoint that returns weather information based on the provided prompt
/weather-streaming - A streaming endpoint that delivers weather information in real-time as it’s being generated

Prerequisites

AWS CLI installed and configured
Node.js (v18.x or later)
Python 3.12 or later
Either:
- Podman installed and running
- (or) Docker installed and running

Project Structure

lib/ - Contains the CDK stack definition in TypeScript
bin/ - Contains the CDK app entry point and deployment scripts:
- cdk-app.ts - Main CDK application entry point
docker/ - Contains the Dockerfile and application code for the container:
- Dockerfile - Docker image definition
- app/ - Application code
- requirements.txt - Python dependencies for the container & local development

Setup and Deployment

Install dependencies:

# Install Node.js dependencies including CDK and TypeScript locally
npm install

# Create a Python virtual environment (optional but recommended)
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install Python dependencies for the local development
pip install -r ./docker/requirements.txt

Bootstrap your AWS environment (if not already done):

npx cdk bootstrap

Ensure podman is started (one time):

podman machine init
podman machine start

Package & deploy via CDK:

CDK_DOCKER=podman npx cdk deploy

Usage

After deployment, you can access the weather service using the Application Load Balancer URL that is output after deployment:

# Get the service URL from the CDK output
SERVICE_URL=$(aws cloudformation describe-stacks --stack-name AgentFargateStack --query "Stacks[0].Outputs[?ExportName=='AgentServiceEndpoint'].OutputValue" --output text)

The service exposes a REST API endpoint that you can call using curl or any HTTP client:

# Call the weather service
curl -X POST \
  http://$SERVICE_URL/weather \
  -H 'Content-Type: application/json' \
  -d '{"prompt": "What is the weather in New York?"}'

 # Call the streaming endpoint
 curl -X POST \
  http://$SERVICE_URL/weather-streaming \
  -H 'Content-Type: application/json' \
  -d '{"prompt": "What is the weather in New York in Celsius?"}'

Local testing (python)

You can run the python app directly for local testing via:

python ./docker/app/app.py

Then, set the SERVICE_URL to point to your local server

SERVICE_URL=127.0.0.1:8000

and you can use the curl commands above to test locally.

Local testing (container)

Build & run the container:

podman build ./docker/ -t agent_container
podman run -p 127.0.0.1:8000:8000 -t agent_container