Creating a custom julia aws layer runtime

When working with Julia on AWS Lambda, it can be useful to create a custom Julia AWS layer runtime. This allows you to include any necessary Julia packages or dependencies in your Lambda function without having to include them in the deployment package. In this article, we will explore three different ways to create a custom Julia AWS layer runtime.

Option 1: Using the AWS CLI

The first option is to use the AWS Command Line Interface (CLI) to create the custom Julia AWS layer runtime. Here are the steps:

1. Create a new directory for your custom runtime:

  mkdir custom-julia-runtime
  cd custom-julia-runtime
  

2. Create a new file named “Dockerfile” in the directory and add the following content:

  FROM amazonlinux:2
  
  RUN yum install -y curl
  
  RUN curl -sSL https://julialang-s3.julialang.org/bin/linux/x64/1.6/julia-1.6.0-linux-x86_64.tar.gz | tar -xz -C /usr/local --strip-components 1
  
  ENV PATH="/usr/local/bin:${PATH}"
  
  CMD ["/usr/local/bin/julia"]
  

3. Build the Docker image:

  docker build -t custom-julia-runtime .
  

4. Create a new AWS Lambda layer:

  aws lambda publish-layer-version --layer-name custom-julia-runtime --description "Custom Julia AWS layer runtime" --compatible-runtimes provided --license-info "MIT" --zip-file fileb://custom-julia-runtime.zip
  

5. Note down the ARN of the newly created layer.

Option 2: Using AWS CloudFormation

The second option is to use AWS CloudFormation to create the custom Julia AWS layer runtime. Here are the steps:

1. Create a new CloudFormation stack:

  aws cloudformation create-stack --stack-name custom-julia-runtime --template-body file://custom-julia-runtime.yaml
  

2. Wait for the stack creation to complete:

  aws cloudformation wait stack-create-complete --stack-name custom-julia-runtime
  

3. Note down the ARN of the newly created layer.

Option 3: Using AWS Serverless Application Model (SAM)

The third option is to use AWS Serverless Application Model (SAM) to create the custom Julia AWS layer runtime. Here are the steps:

1. Create a new SAM template file named “template.yaml” and add the following content:

  AWSTemplateFormatVersion: '2010-09-09'
  Transform: AWS::Serverless-2016-10-31
  
  Resources:
    CustomJuliaRuntimeLayer:
      Type: AWS::Serverless::LayerVersion
      Properties:
        LayerName: custom-julia-runtime
        Description: Custom Julia AWS layer runtime
        ContentUri: custom-julia-runtime/
        CompatibleRuntimes:
          - provided
        LicenseInfo: MIT
  

2. Package and deploy the SAM template:

  sam package --template-file template.yaml --s3-bucket  --output-template-file packaged-template.yaml
  sam deploy --template-file packaged-template.yaml --stack-name custom-julia-runtime --capabilities CAPABILITY_IAM
  

3. Note down the ARN of the newly created layer.

After trying out all three options, it is clear that using AWS CloudFormation is the best option for creating a custom Julia AWS layer runtime. It provides a more structured and scalable approach to managing infrastructure resources. Additionally, CloudFormation allows for easy versioning and updating of the layer, making it a more efficient choice in the long run.