AWS Lambda or Docker?

AWS Lambda is a serverless compute service offered by Amazon Web Services (AWS) that allows developers to run their code without worrying about servers, scaling, or infrastructure. Lambda supports several programming languages such as Java, Python, and Node.js, and can be triggered by events such as changes to an Amazon S3 bucket or an Amazon DynamoDB table. However, can AWS Lambda run Docker containers?

The answer is yes. AWS Lambda now supports running Docker containers as an alternative to running functions written in a programming language. This feature, called AWS Lambda Layers with Custom Runtimes, allows you to package and deploy your Docker container as a Lambda Layer and use it to execute your code.

Using AWS Lambda with Docker containers has several benefits, including:

1. Easy portability: Docker containers can be easily moved between environments and platforms, making it easier to build, test, and deploy your Lambda functions.
2. Greater flexibility: Docker containers allow you to include dependencies and other components in your Lambda function that may not be available in the Lambda execution environment.
3. Easier management: With Docker containers, you can manage your Lambda functions using familiar tools such as Docker Compose and Docker Swarm, making it easier to monitor and manage your serverless applications.
4. Better performance: Using Docker containers can provide better performance for your Lambda functions since you can control the environment in which your code runs.

To use Docker containers with AWS Lambda, you need to create a custom runtime using a Lambda Layer. This custom runtime is a container image that includes the language runtime, the libraries and dependencies required by your function, and the code that runs your function. The custom runtime can be created using tools such as AWS SAM CLI or Dockerfile.

Once you have created your custom runtime, you can use it to run your Lambda functions by specifying the ARN of the Lambda Layer containing your custom runtime in the Layers property of your function.

In conclusion, AWS Lambda now supports running Docker containers as an alternative to running functions written in a programming language. This feature provides several benefits, including easy portability, greater flexibility, easier management, and better performance. Using Docker containers with AWS Lambda requires creating a custom runtime using a Lambda Layer, but once created, it provides a powerful and flexible way to build and deploy serverless applications.