SWE | CKA | CKS | AWS

Abu Talha  • Peerlist

Tech Stack: Python, Django, Azure 
• Built a REST API w/ Django Rest Framework which generates a CSV formatted response of all github users info
retrieved from given search query. Hosted on Azure Web App Service.
• Utilized the GitHub API and web scraping to implement the functionality to take input such as keywords(coding
lang, followers, repo stars etc.) and location to search for potential employees and retrieve their name, email, location.

GitHire

Tech Stack: Nodejs, MongoDB, Docker, AWS 
• Developed a REST API using NodeJS and express.js that performs CRUD operations like sending requested mission
data and writing the data to MongoDB, retrieve and delete selected entries form the database.
• Communicates w/ the SpaceX REST API to populate the historical data of missions to the MongoDB Atlas database.
• Used GitHub Actions to make a continuous integration workflow that builds and tests the code for production.
• Containerized the website using Docker, published it to dockerhub and hosted the container on AWS EC2.

NASA Mission Control

Tech Stack: Nodejs, MongoDB, Docker
Developed a REST API for a social media platform with features like user authentication(jwt token), following and
unfollowing users, posting, deleting posts, liking/unliking posts, and commenting on posts.
• Implemented ACID transactions on MongoDB to ensure data integrity while post creation, deletion, and updates.
• Used Mocha and Chai.js to write API tests and ensure code quality and reliability.
• Containerized the application using Docker for easy deployment and scalability.

Social Media

Tech Stack: Python, FastAPI, MongoDB 
• Developed a real-time monitoring system. Designed with an asynchronous architecture to efficiently handle large
amounts of data, such as polling every store every hour and processing their up-time and downtime.
• Implemented API endpoints - one to trigger report generation and another endpoint to return the status of the report or a CSV with a report output that includes up-time and downtime data extrapolated based on periodic polling ingested and business hours of all stores.