A tool to programmatically build and publish Layers for AWS Lambda.

Instead of manually copy & pasting build instructions for a Lambda Layer into your shell or trying to script your way around, use this tool to automate the process. Given a simple YAML file, it will:

• create a new, clean directory for the lambda layer,
• run specified pre-installation commands,
• Python: install requirements with Pip in a virtual environment,
• Node.js: install dependencies with NPM,
• strip any binaries and libraries in the lambda directory,
• apply global and layer-specific exclusion patterns,
• bundle the remainder up into a ZIP archive.

Then, you can use the tool to publish the new layer (version) on AWS.

For a full introduction, read the introductory blog post.

Here is a simple example:

---
version: '0.3'
default_excludes:
  - '*.dist-info/*'
  - '*.egg-info/*'
  - '*/__pycache__/*'
  - '*.pyc'
layers:
  awesome-numpy:
    description: 'Minimal numpy 1.18'
    runtimes: 'python3.6'
    pre_installs:
      - 'yum install gcc-gfortran'
    requirements:
      - 'numpy==1.18.2'
    excludes:
      - '*/numpy/tests/*'

Then just run:

$ ./layer-tool.py --build awesome-numpy
[...]

$ du -h awesome-numpy.zip
13M

$ ./layer-tool.py --publish awesome-numpy
{
    "Content": {
        "Location": "https://example.com/aws",
        "CodeSha256": "xxQC6FDxg63M5m2UL2cXmChD+dFX7fp61LRrrqmVjGY=",
        "CodeSize": 13590501
    },
    "LayerArn": "arn:aws:lambda:$AWS_REGION:$AWS_ID:layer:awesome-numpy",
    "LayerVersionArn": "arn:aws:lambda:$AWS_REGION:$AWS_ID:layer:awesome-numpy:1",
    "Description": "Minimal numpy 1.18 for python3.7",
    "CreatedDate": "2020-03-28T07:40:49.714+0000",
    "Version": 1,
    "CompatibleRuntimes": [
        "python3.7"
    ]
}

To learn how to use this tool to reduce the size of your layers, read the post about creating a minimal boto3 layer.

The tests directory also serve as examples how to build layers for different runtimes (Python, Node.js).

To match the environment of AWS Lambda functions as closely as possible (especially when you use this tool on non-Linux systems), the tool should be run inside a Docker container. The lambci/lambda Docker image closely resembles the real Lambda environment and is well-suited for this task. Example:

docker run --rm -v "$PWD:/var/task" lambci/lambda:build-python3.7 ./layer-tool.py --build awesome-numpy

Publishing assumes you have previously configured the aws-cli to connect to your AWS account.

Note: Publishing always creates a new version of your layer. For more information see https://docs.aws.amazon.com/lambda/latest/dg/configuration-layers.html .

In addition to the Python dependencies (requirements.txt), this tool currently needs the following command line tools:

• aws-cli (aws)
• find
• zip

Currently, this tool only supports building Python layers with Pip and Node.js layer with NPM. However, it should be fairly straightforward to extend the functionality to other runtimes and package managers.

This software is license under the MIT License. See LICENSE.