Cloud Resume

Project Summary

In this project I developed and deployed a full-stack portfolio website utilizing various AWS services to ensure a secure and scalable solution. The resume website features a JavaScript visitor counter storing data on a DynamoDB database, that is accessed and updated via an API endpoint I made through API-Gateway and AWS Lambda function written in Python. The web assets are stored inside an S3 bucket, which is served via CloudFront distributions with DNS management done through my Route53 hosted zones.

The entire infrastructure is also defined and managed via Terraform.

View resume.ssatwik.click or terraformed-resume.ssatwik.click for the terraformed version

Technologies and Tools

• JavaScript
• JQuery
• AWS S3
• AWS CloudFront
• AWS Route 53
• AWS DynamoDB
• AWS API Gateway
• AWS Lambda (Python)
• AWS CLI
• GitHub Actions
• Terraform

Features

1. Static Website Hosting with AWS S3:

   • Deployed the portfolio website on AWS S3 buckets.
   • Configured bucket policies for public read access.
   • Utilized versioning and lifecycle policies for efficient storage management.

2. Secure Content Delivery with AWS CloudFront:

   • Set up CloudFront to distribute the content globally with low latency.
   • Configured HTTPS for secure data transmission.
   • Implemented custom caching policies to improve performance.

3. Custom Domain with AWS Route 53:

   • Registered and managed a custom domain using Route 53.
   • Configured DNS records to route traffic to the CloudFront distribution.

4. Visitor Counter:

   • Developed a JavaScript-based visitor counter displayed on the website.
   • Visitor data is stored in DynamoDB.
   • Implemented a RESTful API using AWS API Gateway and Lambda functions to interface with the DynamoDB table.
   • Used the boto3 library in Python for seamless integration with DynamoDB.

5. Continuous Integration and Deployment (CI/CD):

   • Utilized GitHub Actions to automate the deployment process.
   • Configured workflows to automate cache invalidation and deployment to S3.
   • Ensured robust deployment by running Python tests for Lambda functions.

6. Security and Best Practices:

   • Ensured AWS credentials were securely managed and excluded from source control.
   • Implemented tests and monitoring to maintain functionality and security.

Architecture

Getting Started

Prerequisites

• AWS Account
• GitHub Account
• Basic knowledge of AWS services, Python, and JavaScript

Installation and Deployment

1. Clone the Repository:

   git clone https://github.com/s000ik/resume-site.git
   cd resume-site

2. Configure AWS CLI:

   aws configure

3. Set Up S3 Buckets:

   • Create an S3 bucket for hosting the website.
   • Upload the website files to the S3 bucket.

4. Set Up CloudFront:

   • Create a CloudFront distribution pointing to the S3 bucket.
   • Configure HTTPS and caching policies.

5. Configure Route 53:

   • Register a custom domain.
   • Set up DNS records to point to the CloudFront distribution.

6. Deploy Lambda Functions:

   • Write and deploy Lambda functions using the boto3 library for DynamoDB integration.
   • Set up API Gateway to expose the Lambda functions as a RESTful API.

7. Configure CI/CD with GitHub Actions:

   • Set up workflows in the .github/workflows directory.
   • Configure actions to automate deployment and cache invalidation.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Acknowledgments

• AWS for providing robust and scalable cloud services.
• The open-source community for the libraries and tools utilized in this project.