Predicting Flight Arrivals with the Apache Kafka Streams API

This post demonstrates how to perform online training and updating of machine learning models using the Kafka Streams API. It details the use of KTables and GlobalKTables to store and apply ML models for real-time predictions, and how to retrain models in real-time as new data becomes available. The post highlights the architectural simplification achieved by integrating ML directly into the streaming pipeline, eliminating the need for separate batch processing clusters.