Breakout Session
With Uber Freight overseeing a staggering billion loads annually, the demand for real-time analytics is paramount. Delve into our journey as we transitioned from traditional data aggregation methods reliant on stored procedures to a dynamic real-time application powered by Apache Kafka and Flink. Explore on how this innovative architecture revolutionized our operations, slashing data aggregation latency from fifteen minutes to mere seconds. Â
  In this engaging talk, we will spotlight on two key pillars: crafting resilient streaming pipelines leveraging Apache Kafka and the implementation of agile real-time processing jobs with Apache Flink. Join us as we unveil our innovative approach to freight analytics, showcasing a compelling use case that highlights the power of real-time analytics and demonstrates our seamless transition from batch to stream processing