Paolo Patierno, a Principal Software Engineer at Red Hat, explores the integration of various open-source technologies to process and monitor Formula 1 telemetry data in real-time using a cloud-native environment. Leveraging tools like Apache Kafka, Strimzi, Grafana, and InfluxDB, the article outlines how simulated F1 telemetry data from the F1 2020 game can be ingested, processed, and visualized. The system uses Apache Camel to route data from UDP to Kafka topics, and the data is then stored in InfluxDB for visualization in Grafana. This setup allows for the real-time analysis of various telemetry metrics such as car speed, engine performance, and driver behavior, providing valuable insights for engineers to enhance vehicle performance. The project underscores the potential of open-source technologies in creating complex, scalable analytics pipelines and is documented in a GitHub repository for public access.