This project was completed as part of 95-702 Distributed Systems (Spring 2025) at Carnegie Mellon University. It demonstrates a fully integrated cloud-native system consisting of an Android mobile app, a Java servlet-based web API, a MongoDB backend, and a web-based analytics dashboard.
This system enables users to search historical U.S. unemployment rates by month and year via a mobile app. The application makes real-time API requests to the U.S. Bureau of Labor Statistics (BLS), logs requests/responses, and displays analytics via a dashboard.
- Built with native Android SDK
- Includes user input fields (
EditText), trigger button (Button), and output display (TextView) - Sends HTTP requests to the backend servlet
- Parses JSON responses from the servlet and displays unemployment rate
- Repeatable and robust user experience
- Receives HTTP requests from Android app at path
/employment - Fetches JSON data from the BLS API
- Extracts and processes unemployment data
- Responds to Android app with a custom JSON payload
- Logs requests and responses with metadata
- Logs each user request into MongoDB with fields:
- Timestamp
- Month and year
- Full request and response payloads
- Parsed unemployment rate
- Parsing success status
- Enables data aggregation for analytics
- Web interface hosted on GitHub Codespaces
- Publicly accessible dashboard displays:
- Average unemployment rate
- API response success rate
- Timeline chart of queried unemployment rates
- Full formatted logs
- Backend deployed using GitHub Codespaces
- Servlet container (Catalina) configured on port
8080 - ROOT.war uploaded and deployed using Maven build flow
- Endpoint made public to support unauthenticated access by Android clients
- MongoDB Atlas used as a managed cloud database
- Android SDK
- Java Servlet API (Tomcat Catalina)
- MongoDB Atlas
- GitHub Codespaces
- BLS Public API
- JSON parsing
- REST API design
- Native Android application (APK or source)
- Java web service (
ROOT.war) - MongoDB-backed logging system
- Live dashboard showing analytics and logs
- Screenshots of deployment and functionality
- Course: 95-702 Distributed Systems
- Semester: Spring 2025
- Instructor: Marty Barrett and Michael McCarthy
- Institution: Carnegie Mellon University