Guruguha Marur Sreenivasa

At Rivian, our mission is to design and build vehicles that inspire and enable sustainable exploration while delivering a seamless, intelligent user experience. Our connected fleet streams real-time telemetry including sensor data that includes location, battery SOC, etc. To turn this firehose of raw information into instant driver alerts and years of searchable insight, we rely on Apache Flink, Kafka. In this talk, we’ll show how we built a scalable, cloud-native stack that powers real-time features and long-term intelligence. Our vehicles generate a continuous stream of telemetry data. To handle this firehose of information, we’ve built a robust stream processing architecture centered around Flink ingestion pipelines. These pipelines process and enrich the data in real time, powering both internal analytics and external customer experiences. One of the standout components of our platform is Event Watch, which is a Flink-powered feature that allows teams and customers to define streaming jobs that detect key events like abnormal battery drain, collision detection or vehicle movement in/out off a geofence. These events trigger mobile push notifications instantly, enabling…