AWS Lambda Layers are the designated feature for managing and sharing common dependencies across multiple functions. A layer is a .zip archive containing libraries or other dependencies. By creating a layer with the shared dependencies, the developer can attach it to all relevant Lambda functions. To update a dependency, the developer only needs to create a new version of the layer and update the functions to use it. This centralizes dependency management, eliminates redundant packaging efforts for each function, and simplifies the update process, directly addressing the problem with the least additional complexity.

A. Lambda does not have a "maintenance window" feature for function code updates; this approach does not solve the core problem of duplicated dependency packaging.

B. Upgrading the Lambda runtime updates the execution environment (e.g., Python version) but does not manage the application-specific dependencies packaged with the function code.

D. Using CodeCommit centralizes the source code but does not solve the problem of packaging and deploying the dependencies into each individual Lambda function's deployment artifact.

1. AWS Lambda Developer Guide

"Using Lambda layers": The documentation states

"You can use layers to keep your deployment packages small

which makes it easier to develop your function code. A layer is a .zip file archive that can contain additional code or data. A layer can contain libraries

a custom runtime

data

or configuration files." This directly supports using layers for shared libraries.

2. AWS Lambda Developer Guide

"Creating and sharing layers": This section explains the core benefit: "By separating common components into layers

you can make it easier to update your functions and share these components across multiple functions." This aligns perfectly with the scenario of updating dependencies for many functions.

3. AWS Well-Architected Framework

Serverless Applications Lens

"Operational Excellence Pillar - OPS 4": The guide recommends

"Separate the business logic from the dependencies... You can use Lambda Layers to separate dependencies from your function code. This simplifies the process of updating dependencies because you don't need to redeploy your function code." This identifies layers as a best practice for the exact problem described.