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Friday, February 19 • 9:45am - 10:10am
Formula 1 telemetry processing using Kafka Streams

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Apache Kafka is the de facto data streaming platform used for ingesting vast amounts of data and processing them in real-time. Low latency analytics are vital if users are to react to events as fast as possible and to effectively shape future decision making. The Apache Kafka upstream community provides the Kafka Streams library for simplifying the development of highly scalable applications for filtering, mapping, transforming, and enriching these data.
During this session, we will explore how we can use Kafka Streams to help a Formula 1 team gain insights during a race. The 'real' data will come from a well-known racing game and will be processed by our application in real-time, making us feel like real track-side F1 engineers!

avatar for Paolo Patierno

Paolo Patierno

Principal Software Engineer, Red Hat
Paolo is a Principal Software Engineer working for Red Hat on the messaging and IoT team. He has been working on different integration projects having AMQP with Apache Kafka and Spark and on the EnMasse messaging-as-a-service project about the integration with MQTT. Currently, he... Read More →
avatar for Thomas Cooper

Thomas Cooper

Senior Software Engineer, Red Hat
Tom has various Computer Science degrees and a PhD in Distributed Streaming Systems. His research focused on performance modelling of streaming systems like Apache Storm and involved digging deep into the nuts and bolts of big data stream processing. He even got to work at Twitter... Read More →

Friday February 19, 2021 9:45am - 10:10am CET
Session Room 4