Formula 1 telemetry processing using Kafka and Camel
Cloud • May 2021
Formula 1 telemetry processing using Kafka and Camel
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About
Formula 1 telemetry processing using Kafka and Camel
About

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. Apache Camel is an integration framework that empowers you to quickly and easily integrate various systems consuming or producing data. During this session, we will explore how we can use these technologies together to help a Formula 1 team gain insights during a race. You will feel like a real track-side F1 engineer!

Language
English
Level
Intermediate
Length
36 minutes
Type
online conference
About the speakers
About the speakers
Paolo Patierno
Principal Software EngineerRed Hat
Paolo is a Principal Software Engineer working for Red Hat on the messaging and IoT team. He is a maintainer of Strimzi, a CNCF sandbox project for running Apache Kafka on Kubernetes using operators. In his previous role, he worked on different integration projects about AMQP with Apache Kafka and Spark and on the EnMasse messaging-as-a-service project about the integration with MQTT. He is also a maintainer for different IoT related components in Eclipse Vert.x and Eclipse Paho projects. Finally, he has spoken at numerous national and international conferences about Kafka, Strimzi, and IoT.
Thomas Cooper
Senior Software EngineerRed 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 for a while with their Heron stream processing system. He now works for Red Hat and develops tools (Strimzi) to help run Apache Kafka on Kubernetes.
Details
Language
English
Level
Intermediate
Length
36 minutes
Type
online conference