How FlightAware fuels flight prediction models for global travelers with TimescaleDB and Grafana

This installment of the "Community Member Spotlight" series features Caroline Rodewig, Senior Software Engineer and Predict Crew Lead at FlightAware, who shares how they've architected a monitoring system that allows them to power real-time flight predictions, analyze prediction performance, and continuously improve their models. The system uses TimescaleDB and Grafana for data storage and visualization, respectively. FlightAware's predictive technologies team is responsible for developing the predictive applications, which are powered by the monitoring system. The team has set up a simple architecture that includes custom Python programs, Docker, Grafana, and TimescaleDB. They use continuous aggregates to improve query performance, reducing execution time from 6.4 seconds to 30 milliseconds. Caroline's experience with TimescaleDB was instrumental in implementing this system, which has enabled FlightAware to provide accurate, reliable flight data to travelers, aviation enthusiasts, and operators worldwide.

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