Lambda Containers

AWS Lambda originally supported ZIP file deployments, and now you can also upload container images—combining the portability of Docker with Lambda’s serverless execution model. With container images, you package your application code, dependencies, and configuration into a single, portable image. AWS then runs that image in a fully managed, serverless environment without you needing to manage servers or clusters.

Why Use AWS Lambda Container Images?

Running containers on Lambda delivers the following advantages:

Large Image Support

Lambda container images support sizes up to 10 GB, so you can bundle large frameworks, machine learning models, or data-processing libraries.

Building and Deploying Your Lambda Container

To deploy a container image on Lambda, your Docker image must include the Lambda Runtime Interface Client (RIC) or Runtime Interface Emulator for local testing.

AWS provides several official base images:

Here’s a sample Dockerfile that uses the Python 3.9 managed runtime base image:

# Dockerfile example
FROM public.ecr.aws/lambda/python:3.9

# Copy application code
COPY app.py ${LAMBDA_TASK_ROOT}

# Set the command to run your handler
CMD ["app.handler"]

After building and pushing your image to Amazon ECR, simply create or update a Lambda function to point to that image:

aws lambda create-function \
  --function-name my-container-function \
  --package-type Image \
  --code ImageUri=123456789012.dkr.ecr.us-east-1.amazonaws.com/my-image:latest \
  --role arn:aws:iam::123456789012:role/lambda-execution-role

Conclusion

By leveraging container images on AWS Lambda, you get the portability and tooling of Docker combined with a fully managed, auto-scaling, pay-per-use serverless environment. Whether you’re running microservices, data-processing jobs, or AI workloads, Lambda Containers offer flexibility and simplicity.

Links and References

• AWS Lambda Container Images
• Lambda Runtime Interface Client (RIC)
• Lambda Runtime API