Why flight data is deceptively difficult
A flight looks like one record to a traveler, but live aviation data is fragmented across callsigns, flight numbers, registrations, airports, routes, and changing positions. I built Flight Tracker because I wanted to create a product that could take a natural question and resolve it into a stable view of a flight, airport, or route. The experience needed to feel simple even though the data underneath it was anything but simple.
Resolving intent into canonical pages
I created a routing layer that interprets a query and maps it to a canonical URL. That decision keeps the interface shareable and prevents every search from becoming temporary state. A query might refer to a flight number, an airport code, or a route, so the resolver has to classify the intent, normalize identifiers, and handle ambiguity before the page requests live data.
Fusing live telemetry
The platform combines information from Flightradar24, ADS-B.lol, OpenSky, and adsbdb. I mapped provider-specific responses into one flight model with source and freshness metadata. A custom phase classifier uses available telemetry to estimate whether an aircraft is climbing, cruising, descending, or on the ground. Leaflet renders geospatial movement, while airport boards turn individual records into an operational view.
Designing for imperfect skies
Live providers rate-limit, disagree, and return partial records. I added timeouts, fallbacks, caching, and clear unavailable states so one source failure would not collapse the whole experience. This build taught me that real-time software is an exercise in honest uncertainty. The most trustworthy interface is not the one that always looks live. It is the one that tells the user what is current, what is inferred, and what could not be confirmed.