Taking KSQL for a Spin Using Real-time Device Data

This post details the process of setting up a real-time data pipeline using a gaming device as a data source, Apache Kafka for ingestion, and ksqlDB for real-time stream processing and analysis. It covers writing a custom Kafka producer using C# and the Confluent .NET Kafka Client to capture device inputs (steering, braking, acceleration) and send them as JSON messages to Kafka. The post then demonstrates how to create ksqlDB streams from the raw Kafka topic, filter and transform the data (e.g., converting raw axis values to degrees or percentages), and create derived streams for specific inputs like steering, accelerator, and brake. The final output is visualized in Grafana, showcasing the real-time dashboard. This post highlights the low-latency, high-throughput capabilities of Kafka and ksqlDB for IoT-like scenarios.