Fleets in various industries generate vast amounts of real-time telemetry data, which can be used to build fleet management solutions that simplify operations and improve customer experience. To process this data, a combination of Confluent Cloud, fully managed ksqlDB, Kafka Connect with MongoDB connectors, and MongoDB Atlas is used. The solution utilizes Voluble to mock telemetry data and integrates it with MongoDB for historical analysis. Stream processing complements various use cases in fleet management, including hazard detection, route optimization, and real-time alerting. A ksqlDB application processes events in real-time, detecting hazardous driving patterns and generating notifications. The system also captures real-time location data and harsh-braking events from the fleets, exporting them to MongoDB for further analysis and visualization. Confluent Cloud and MongoDB work well together in designing an overall fleet management solution, especially as autonomous fleets and advanced delivery systems become more prevalent.