AWS Cloud Resume API

This project will guide you through building and deploying a serverless API using AWS Lambda and DynamoDB, integrated with GitHub Actions and Terraform . The primary goal is to construct an API that serves resume data in JSON format and make it accessible on the internet using API Gateway .

Demo

curl https://lpn6ekqu21.execute-api.us-east-1.amazonaws.com/prod/resume

Overview

This project automates the deployment of an AWS Lambda function using Terraform and GitHub Actions. The Lambda function serves as the backend for a resume API, providing endpoints to fetch resume details stored in a dynamoDB table .

Architecture

The architecture involves:

• AWS Lambda: Runs the backend code for the API.
• AWS API Gateway: Provides a RESTful API endpoint.
• DynamoDB: Stores the json resume data.
• Terraform: Manages the infrastructure as code.
• GitHub Actions: Automates the CI/CD pipeline.

Prerequisites

Before you begin, ensure you have met the following requirements:

• An AWS account with necessary permissions.
• Terraform installed.
• AWS CLI configured with your credentials.
• A GitHub account with access to the repository.

Structure of the Project

AWS-CLOUD-RESUME-API/
├── .github/
│   └── workflows/
│       └── deploy.yml
├── src/
│   ├── lambda_function.py
│   └── lambda_function.zip
├── .gitignore
├── main.tf
├── provider.tf
├── README.md
├── requirements.txt
└── resume.json

Project setup steps 🚀

1. Set Up AWS

• Sign Up for AWS: If you don't already have an AWS account, sign up at aws.amazon.com.
• Set Up Credentials: Configure your AWS CLI with your credentials using aws configure.

2. Create a JSON Resume

• Create a JSON file containing your resume data. Follow a schema Here
• Store this JSON file for later use.

3. Create DynamoDB Table

• Table Name: Resumes
• Primary Key: id (String)
• Populate the table with your resume data using the AWS Management Console, AWS CLI, or a script.

4. Write the Lambda Function

• Create a Python script (lambda_function.py) to fetch resume data from DynamoDB and return it in JSON format.

5. Package the Lambda Function

• Zip the lambda_function.py file.

6. Create Terraform Configuration

• Create main.tf and provider.tf for infrastructure as code as a way to automatically create the lambda function and the API Gateway configurations .

7. Create an S3 bucket to store terraform state files

• Create an S3 bucket in the AWS console or the AWS CLI with the same name as the one used in provider.tf file .

7. Apply Terraform Configuration

• Initialize Terraform:

  terraform init

• Plan the Deployment:

  terraform plan

• Apply Deployment:

  terraform apply

• After the deployement an api endpoint url is going to be generated , keep it for the test after .

8. Set Up GitHub Actions

• Create a GitHub Actions workflow (.github/workflows/deploy.yml) to automatically deploy updates to your Lambda function on every push to the repository.

9. Test the API

• API Gateway URL: Test your endpoint to ensure it returns the resume data in JSON format (the one generated after executing the terraform setup) using curl.
• GitHub Actions: Make a change to your code, push to the repository, and verify that the GitHub Actions workflow deploys the updated Lambda function.

Medium Blog

• For a detailed step by step guide to build this project , follow the steps in this blog