Serverless Image Processing with AWS Lambda and Terraform

This project sets up a serverless infrastructure for image processing using AWS Lambda, Terraform, and Node.js. The infrastructure is provisioned using Vagrant and Terraform, and the Lambda function is written in Node.js.

Table of Contents

• Prerequisites
• Installation
• Configuration

Prerequisites

• Vagrant
• VirtualBox
• Terraform
• AWS CLI
• Node.js

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/your-repo.git
   cd your-repo

2. Set up environment variables:

   Make sure you have the following environment variables exported in your shell with your AWS Credentials

   AWS_ACCESS_KEY_ID=your_access_key_id
   AWS_SECRET_ACCESS_KEY=your_secret_access_key
   AWS_REGION=your_aws_region

3. Run Vagrant to provision the infrastructure:

   vagrant up

   This will execute the init.sh script to install necessary tools and set up the infrastructure.

Key Files and Directories

• init.sh: Script to set up the environment and install necessary tools.
• function/: Contains the Node.js Lambda function code.
• terraform/: Contains Terraform configuration files for provisioning AWS resources.
• .github/workflows/main.yml: GitHub Actions workflow for deploying the infrastructure.

Configuration

The configuration for the Lambda function and other resources is managed through Terraform variables. These variables are defined in terraform/modules/lambda/variables.tf and can be set in the .github/workflows/main.yml file or terraform/terraform.tfvars if you're working locally.

Example Variables

env:
    TF_VAR_lambda_function_name: "webp_convert"
    TF_VAR_lambda_runtime: "nodejs18.x"
    TF_VAR_lambda_handler: "index.handler"
    TF_VAR_lambda_src_code: "../function"
    TF_VAR_lambda_zip: "./lambda.zip"
    TF_VAR_original_files_bucket_name: "bucket-orginal-file"
    TF_VAR_edited_files_bucket_name: "bucket-edit-file"