Deploy FastAPI to AWS Lambda with Mangum

FastAPI is a modern Python web framework. It is known for its speed and ease of use. AWS Lambda is a serverless compute service. It runs your code without managing servers.

Combining them is powerful. You get scalable APIs with low cost. Mangum is the bridge that makes this possible. It adapts FastAPI for the Lambda environment.

This guide will walk you through the entire process. We will cover setup, deployment, and best practices.

Why Use FastAPI with AWS Lambda?

Serverless architecture offers many benefits. You only pay for the compute time you consume. There is no need to provision or manage servers.

Scaling is automatic. Lambda handles thousands of requests seamlessly. FastAPI adds high performance and automatic documentation.

Together, they create a perfect backend solution. It is ideal for APIs with variable traffic. Startups and enterprises both benefit.

Understanding the Mangum Adapter

Mangum is a Python library. It adapts ASGI applications to run on AWS Lambda. ASGI is the async server gateway interface.

FastAPI is an ASGI framework. Mangum wraps your FastAPI app. It translates Lambda events into ASGI scope.

This allows Lambda to understand FastAPI requests. The Mangum class is the key component. You create a handler from your app instance.

Project Setup and Dependencies

First, create a new project directory. Set up a virtual environment inside it. This isolates your project dependencies.

Install the required packages. You will need fastapi, mangum, and uvicorn for local testing. Use pip to install them.

# Create and activate a virtual environment
python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`

# Install dependencies
pip install fastapi mangum uvicorn
    

Creating a Basic FastAPI Application

Create a main application file. We will build a simple API with two endpoints. One for a health check and one to fetch items.

This example is minimal. It demonstrates the core structure. You can expand it later with more features.

# main.py
from fastapi import FastAPI
from mangum import Mangum

# Initialize the FastAPI app
app = FastAPI(title="Serverless FastAPI")

# Define a simple health check endpoint
@app.get("/health")
async def health_check():
    return {"status": "healthy"}

# Define an endpoint that returns a list of items
@app.get("/items/{item_id}")
async def read_item(item_id: int, q: str = None):
    return {"item_id": item_id, "q": q}

# Create the Mangum handler for AWS Lambda
handler = Mangum(app)
    

Testing the Application Locally

Before deploying, test your API locally. Use uvicorn to run the development server. This ensures everything works.

Start the server and make requests. You can use curl or a browser. Check both endpoints for correct responses.

# Run the FastAPI app locally with uvicorn
uvicorn main:app --reload

# In another terminal, test the endpoints
curl http://127.0.0.1:8000/health
curl "http://127.0.0.1:8000/items/5?q=test"
    

# Expected output from /health
{"status":"healthy"}

# Expected output from /items/5?q=test
{"item_id":5,"q":"test"}
    

Preparing for AWS Lambda Deployment

Lambda requires all dependencies packaged. You cannot rely on system packages. Create a deployment package.

First, generate a requirements.txt file. This lists all project dependencies. Use pip freeze for accuracy.

# Generate requirements.txt
pip freeze > requirements.txt
    

Your project structure should look like this. Keep it clean and organized.

my_fastapi_app/
├── main.py
└── requirements.txt
    

Deploying with the AWS Management Console

This method is good for beginners. You use the AWS web console. It provides a visual interface.

First, log into your AWS account. Navigate to the Lambda service. Click "Create function".

Choose "Author from scratch". Give your function a name. Select Python as the runtime.

You must create a deployment package. Zip your main.py and dependencies. Then upload the zip file.

Set the handler to main.handler. This points to the Mangum instance. Finally, create an API Gateway trigger.

Configure the trigger to create a new HTTP API. This exposes your Lambda function as a web endpoint.

Deploying with the AWS CLI and SAM

The CLI is better for automation. SAM (Serverless Application Model) simplifies deployment. It uses a template.yaml file.

First, install and configure the AWS CLI. Ensure you have credentials set up. Then install the SAM CLI.

Create a template.yaml file in your project. This defines your Lambda function and API Gateway.

# template.yaml
AWSTemplateFormatVersion: '2010-09-09'
Transform: AWS::Serverless-2016-10-31

Resources:
  FastAPIFunction:
    Type: AWS::Serverless::Function
    Properties:
      CodeUri: ./
      Handler: main.handler
      Runtime: python3.9
      Events:
        ApiEvent:
          Type: Api
          Properties:
            Path: /{proxy+}
            Method: ANY
    

Now use the SAM CLI to build and deploy. It packages your code and uploads it to S3. Then it creates the CloudFormation stack.

# Build the deployment package
sam build

# Deploy the application
sam deploy --guided
    

After deployment, SAM provides the API endpoint URL. Use this URL to test your live FastAPI application.

Key Configuration and Best Practices

Lambda has specific settings. Configure memory and timeout appropriately. FastAPI is fast, but complex logic may need more time.

Set environment variables for configuration. Never hardcode secrets. Use AWS Systems Manager Parameter Store.

Enable CloudWatch Logs for monitoring. This is crucial for debugging. Check logs for errors and performance data.

Use API Gateway stages for versioning. This helps manage different environments. For example, dev, staging, and prod.

Consider using a FastAPI Performance Optimization Guide to keep your Lambda function efficient. Cold starts can be mitigated with provisioned concurrency.

Handling Advanced FastAPI Features

Mangum supports most FastAPI features. This includes background tasks, dependencies, and middleware.

For database operations, use async connections. Our guide on FastAPI Async Database with asyncpg SQLAlchemy is very helpful. It ensures non-blocking database calls.

Implement proper error handling. Use FastAPI's exception handlers. This gives users clear error messages.

You can also customize your API docs. Learn how in our article on Customize FastAPI Swagger UI and ReDoc. This improves the developer experience.

Testing the Deployed API

Once deployed, test your endpoints. Use the provided API Gateway URL. Make GET and POST requests as needed.

Test the health check endpoint first. Then test the items endpoint with parameters. Verify the responses match expectations.

# Example test with curl (replace with your URL)
curl https://your-api-id.execute-api.region.amazonaws.com/Prod/health
curl "https://your-api-id.execute-api.region.amazonaws.com/Prod/items/10?q=hello"
    

Conclusion

Deploying FastAPI to AWS Lambda with Mangum is straightforward. It combines a great framework with serverless power.

You get automatic scaling and reduced operational overhead. The cost model is pay-per-use, which is efficient.

Start with a simple API. Then add more complex features as needed. Use the guides linked for advanced topics.

Remember to monitor performance and costs. AWS provides all the tools you need. Happy building your serverless APIs!