Ray can be paired with Apache Kafka to power streaming applications. Data processing needs are far outpacing the development of faster hardware, driving a transition from vertical scaling to horizontal scaling. Event streaming platforms have emerged to capture and react to events in real-time, often acting as distributed logs that allow applications to produce and consume data horizontally. However, distributing stream processing to keep up with production rates is not easy, as the rate of production can vary drastically, requiring manual sizing that often results in suboptimal behavior due to wasted resources or slow reactions to peak demands. Ray Clusters can alleviate these issues by autoscaling to meet the demands of a stream processing job, ensuring efficient use of resources and delivering a "serverless" experience.