Starlink Performance Globe
A full-stack 3D globe that combines real Starlink latency data, live satellite orbits, and regional congestion modeling — built from 31M+ measurements, ~9,600 satellites, and ~100 regions.
Dataset construction
Built a reproducible latency dataset from M-Lab NDT7 in BigQuery (SpaceX ASN, min RTT per grid cell), then served layers from FastAPI and rendered them as WebGL hex tiles with utilities for antimeridian and polar edge cases.
Real-time orbital simulation
Ingested TLE data and propagated ~9,615 satellites in-browser with continuous client-side updates. Hourly refresh, caching, and invalid-output filtering keep the layer reliable without per-frame server calls.
Congestion modeling
Regional pipeline combining Cloudflare Radar traffic, usage assumptions, diurnal demand, and orbital density to estimate demand. Supply from visible satellite counts and altitude-based capacity — demand vs. capacity across ~100 regions.
Production and operations
Containerized Python backend on Render, frontend on Vercel, with background jobs for data refresh and keep-alive so the demo stays up on free tier.