AWS Lambda Layers play a crucial role in simplifying the deployment process for Lambda functions. They provide an easy way to collect and manage Python packages as AWS Lambda ( $\lambda$ ) Layers, streamlining the development workflow. In this article, we'll explore how to use pre-existing Lambda Layers and create custom layers from scratch using Flask as an example.

Keith's Layers for Easy Deployment

If you're looking for readily available Lambda Layers, keith's Layers is a fantastic resource. These layers make it incredibly convenient to deploy Python packages for AWS Lambda. You can quickly access a collection of Python Packages as AWS Lambda Layers, making the deployment process much more straightforward.

Creating your own Custom Layers

Creating a custom Lambda Layer tailored to your specific needs is a powerful approach. Let's walk through the four main steps to create a Lambda Layer with Flask:

Setting up the Local Directory for the Layer

To begin, create a local directory for the Lambda Layer. In this example, we'll use Flask. Execute the following commands:

mkdir flask-layer
cd flask-layer
mkdir -pv python/lib/python3.8/site-packages

This creates a directory named flask-layer with a subdirectory python/lib/python3.8/site-packages, where we'll install our Python packages.

Adding the Requirements File

Next, create a requirements.txt file in the root of the flask-layer folder, specifying the required packages. For instance, for Flask, the requirements.txt may contain:

flask==1.1.1

The file structure should now look like this:

flask_layer
├── python
|   └── lib
|       └── python3.8
|           └── site-packages
└── requirements.txt

Installing Requirements with Docker

To install the requirements in the local directory using Docker, run the following command in powershell when you are in root directory

docker run -v ${pwd}:/var/task "amazon/aws-sam-cli-build-image-python3.8" /bin/sh -c "pip install -r requirements.txt -t python/lib/python3.8/site-packages; exit"

This command populates the site-packages directory you created earlier with all the necessary dependencies.

Uploading Your Custom Layer to AWS

AWS requires all the layer code to be in a zip archive, so we need to zip everything in the python directory:

zip -r flask-layer.zip python

Now the layer can be uploaded to AWS using the AWS CLI. You need to provide a few parameters in this step:

layer-name is the name your want to give your layer
description to briefly summarize the layer
zip-file is the path to the zip archive you created in the previous step
compatible-runtimes details the Python versions your layer is compatible with

Use the following terminal command to publish your custom layer to AWS:

aws lambda publish-layer-version \
    --layer-name "flask-layer" \
    --description "Lambda Layer for Flask 1.1.1" \
    --zip-file "fileb://flask-layer.zip" \
    --compatible-runtimes "python3.8"

With these steps, you can create a custom Lambda Layer tailored to your application's needs, enhancing the efficiency and maintainability of your AWS Lambda functions.