Constellarium

Overview

Constellarium is a full-stack web application that lets users explore the night sky in 3D — navigating through zodiac constellations, discovering over 300,000 stars, and asking an AI chatbot questions about each constellation they visit.

The project covered the complete full-stack developer workflow: local development, deployment, and server maintenance.

Problem

The course brief was explicitly about server infrastructure — but building a CRUD app felt like a missed opportunity. The goal was to find a subject matter compelling enough to justify a rich frontend while still fulfilling the backend and deployment requirements rigorously.

Process

We built and integrated three distinct layers:

Frontend: Three.js powers the 3D star map. Users are placed at the center of the zodiac, with all constellations surrounding them. Clicking a constellation navigates to a detail page. A performance mode allows adjusting the number of rendered stars — this was necessary to support lower-end hardware without compromising the experience on capable devices.

Backend: A Node.js server handles API routing, data serving, and OpenAI integration. The star database (300,000+ entries) is stored in MongoDB and queried efficiently with indexed lookups.

AI integration: Each constellation detail page includes a chatbot powered by OpenAI. The prompt is seeded with the constellation's context — mythology, location, notable stars — so responses are specific and accurate rather than generic.

Deployment: The full stack is hosted separately (frontend, backend, database). GitHub Actions automates CI/CD; Portainer manages containerized services; Termios handles server access and monitoring.

Solution

The result is an immersive, educational experience that treats astronomy as a subject worth exploring deeply. Users move through a 3D representation of the sky, read curated constellation information, and can go further by asking the AI follow-up questions — all within a single, coherent application.

Outcome

Constellarium proved that strong subject matter makes technical work more meaningful. The deployment pipeline in particular was a steep learning curve — understanding how GitHub Actions, Docker, and a live server interact required systematic debugging and documentation. That operational knowledge now informs how I think about building for production, not just for development.