For the last decade, one aircraft has quietly lived far from the skies it once called home.

5Y-KZX, a Kenya Airways Boeing 777-300ER, has been away in Turkey for years, operating outside the familiar rhythm of East African routes. But now, something feels different. The aircraft is preparing for a return, rejoining the long haul network it once served, with upcoming rotations to Johannesburg and London beginning on the 3rd of July.

As someone deeply fascinated by aviation, I cannot help but feel a sense of excitement watching this unfold in real time.

A personal connection to aviation

I have always been drawn to aircraft.

Not just as machines, but as moving systems of engineering, coordination, and global connection. There is something almost poetic about how a single aircraft can link cities, cultures, and people across continents.

Tracking flights has become more than a technical exercise for me. It is a way of understanding movement at a global scale, and appreciating the invisible infrastructure that keeps the world connected.

KQ Flight Tracker (5Y-KZX)

A real time aircraft tracking system built on AWS that monitors Kenya Airways Boeing 777-300ER (5Y-KZX) using OpenSky Network data. The system behaves like a simplified Flightradar-style dashboard, showing live aircraft movement, flight state, and historical tracking.

Architecture

OpenSky API → AWS Lambda → DynamoDB → API Gateway → S3 Frontend (Leaflet Map)

Building a real time flight tracking system

This journey inspired me to build a cloud based aircraft tracking system using AWS.

The idea is simple:

• Pull live aircraft data from OpenSky Network
• Track 5Y-KZX in real time using AWS Lambda
• Store flight positions in DynamoDB
• Detect flight states such as departure, cruising, and arrival
• Visualize everything on a live map dashboard

In many ways, it feels like building a personal version of Flightradar24, but tailored to a single aircraft that I care about.

Flight state intelligence

One of the most interesting parts of the system is flight state detection.

Instead of just showing coordinates, the system interprets movement:

• DEPARTED: when the aircraft leaves its origin region
• CRUISING: when it is en route over long distances
• ARRIVING: when it approaches Kenyan airspace
• LANDED: when it reaches JKIA

This transforms raw flight data into meaningful storytelling.

Why this matters

Real time aviation data is powerful, but often overwhelming when viewed globally.

Focusing on a single aircraft creates clarity. It turns noise into narrative and movement into something observable in a meaningful way.

This project sits at the intersection of cloud engineering and aviation curiosity, combining data ingestion, serverless compute, and frontend visualization.

Challenges
1.Managing API rate limits during frequent data requests
2.Filtering global flight data down to a single airline
3.Ensuring smooth map updates without performance issues
4.Handling inconsistent aircraft metadata across sources

GitHub Repository

The full source code, architecture, and implementation details for this project are available on GitHub:
https://github.com/Copubah/kq-flight-tracker