How to Share Code Between Several Lambda Functions in AWS

Discover effective strategies for code sharing among Lambda functions in AWS, including the use of Lambda Layers and practical coding examples.
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How to Share Code Between Several Lambda Functions in AWS

In the world of serverless computing, efficiency and reusability of code are critical for maintaining clean and cost-effective applications. If you're working with AWS Lambda and have multiple functions that require access to shared code, you might be wondering how to streamline this process. This guide explores the best practices for sharing code between several Lambda functions, including the use of Lambda Layers and alternative methods.

The Challenge of Code Reusability

When building microservices with numerous Lambda functions, code duplication can quickly lead to messy and hard-to-maintain codebases. Let’s say your project has a folder structure like this:

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Solution Overview: AWS Lambda Layers vs. Direct Imports

Using AWS Lambda Layers

AWS Lambda Layers are a powerful feature designed to facilitate code sharing across different Lambda functions. Here are some situations when you should consider using them:

Version Control: If your shared code is expected to change over time, utilizing layers allows you to manage versioning separately from your Lambda functions. This is particularly useful for your operations team, who may need to update shared code without influencing the deployment of the Lambda functions.

Large Dependencies: When shared code is substantial, bundling it within each function may inflate the function's size unreasonably. Layers help keep your Lambda packages lean by keeping shared code separate.

No Deployment System: If you're not using automated deployment tools like Pulumi or Terraform, layers provide an easy way to handle shared resources.

Direct Imports

However, Lambda Layers are not the only solution, and there are scenarios where direct imports might be more beneficial:

Stable Dependencies: If the code you want to share is not expected to change frequently and doesn't require versioning, simply importing the necessary functions can be a more straightforward approach.

Small Code Bases: If the shared dependency is relatively minor and doesn't merit the complexity of dealing with layers, direct inclusion can simplify the development process.

Example Code

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Now you can easily import these functions in your handler files:

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The build process is smart enough to perform Tree Shaking, ensuring that only the relevant code is packaged with your Lambda function.

Conclusion

In conclusion, while AWS encourages the use of Lambda Layers for sharing code between Lambda functions, it is not an absolute requirement. Depending on your project's needs and constraints, you can either utilize layers for versioned and larger shared dependencies or opt for direct imports for smaller, static pieces of code.

By understanding the benefits and drawbacks of each approach, you can make informed choices that will enhance the maintainability and efficiency of your serverless applications. Happy coding!