Deploying Julia Programs on AWS Lambda: A Step-by-Step Guide

Julia is a high-performance, open-source programming language that is gaining popularity in the world of data science and scientific computing. If you're a Julia developer looking to deploy your programs on the cloud, AWS Lambda is a great option. In this blog post, we'll walk you through the steps to deploy a Julia program on AWS Lambda using Docker and Terraform.

Step 1: Write the Julia Code
The first step is to write the Julia code for your program. In this example, we'll use a simple program that calculates the factorial of a given number.

function factorial(n)
    if n == 0
        return 1
    else
        return n * factorial(n-1)
    end
end

println(factorial(5))

Step 2: Create a Docker Container
The next step is to create a Docker container for your Julia program. This will allow you to easily deploy the program on AWS Lambda. In this example, we'll use the official Julia Docker image and add our program to the container.

FROM julia:latest

COPY factorial.jl /factorial.jl

CMD ["julia", "/factorial.jl"]

Step 3: Create an AWS Lambda Function
Once the Docker container is ready, you can use Terraform to create an AWS Lambda function and deploy the container. Here's an example of the Terraform code you can use:

resource "aws_lambda_function" "example" {
  function_name = "example"
  runtime = "provided"
  handler = "factorial.jl"
  role = aws_iam_role.lambda_exec.arn
  filename = "docker-container.zip"
  source_code_hash = filebase64sha256("docker-container.zip")
}

Step 4: Test the Lambda Function
Finally, you can test your AWS Lambda function to make sure it's working as expected. You can do this by invoking the function using the AWS Lambda console or the AWS CLI.

In conclusion, deploying Julia programs on AWS Lambda is a simple process that requires writing Julia code, creating a Docker container, and using Terraform to deploy the container as an AWS Lambda function. With this guide, you should be able to deploy your Julia programs on the cloud in no time.