The goal of this capstone project was to create the back end of the "Questions and Answers" service of a mock fashion website that can scale to the demands of production traffic.
- RESTful API to handle requests to a MongoDB database
- ETL (Extract, Transform, Load) process from csv files consisting of over six million records containing flawed data
- Designed and built an API server to provide data to the client in the format specified by the API documentation
- Optimized database and query methods for speed and response
- Deployed using Docker-Compose and AWS EC2 t2.micro instances
- Stress tested all API routes, checking for RPS (requests per second), latency, and error rate
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This can be readily used as a teaching tool for using Docker-Compose to quickly deploy a full stack application. Simply clone down, open your Docker desktop, and run docker compose up to spin up images for 🙆♀️ the frontend client, 📬 the server, and 📂📂 a MongoDB-powered database. Alternatively, uncomment out line 4 and comment out line 5 of docker-compose.yml in order to see the Dockerfile in action.