Neil Buesing

You want to develop data‑streaming applications with Kafka Streams, a Java library, but you’ve been told they consume too many resources when deployed in your Kubernetes cluster. Your organization is moving away from Java due to memory consumption and CPU utilization concerns. You’re also using a cloud‑based Kafka cluster with limits on the number of active connections. If any of these issues are being raised in your organization, come learn practical ways to reduce your memory footprint, improve CPU performance, and rein in Kafka connections. Even if you are just using consumers and producers, you will still gain insights to make them more efficient. Leave with a clear understanding of Java 25 features in action, whether GraalVM can work for you, how to tune RocksDB, how to use stream threads effectively, how to manage connection counts, and more. Retain the rich ecosystem of Java with its 30 year history and Kafka Streams with its 10 year history.

My breakout session is a choose-your-own-adventure style presentation, where the audience selects which Kafka Streams topologies will be covered. This presentation will cover topologies not covered in my breakout session, again by audience selection. There will still be plenty of topologies to choose from. If you are new to Kafka Streams or an advanced user, you will have fun and learn a few things about Kafka Streams.

Event streaming with Kafka Streams is powerful, but can feel overwhelming to understand and implement. Breaking down ​​advanced concepts into smaller, single-purpose topologies makes learning more approachable. Kafka Streams concepts will be introduced with an interactive web application that allows you to visualize input topics, output topics, changelog topics, state stores, and more. What happens when state store caching is disabled? What if topology optimization is enabled? Or what if stream time isn't advanced? These questions will be easily explored by visualizing the topology and Kafka Streams configurations. This interactive tutorial's real-time events are generated by actual data on your laptop, including running processes, thread details, windows, services, and user sessions. Moving a window on your laptop can trigger many examples, allowing you to see how the topology handles them. The audience will select which topologies to cover in categories of: flow, joins, windowing, advanced state storage usage, and more. Join me on this ​​journey of learning Kafka Streams. You'll deepen your understanding of Kafka Streams concepts and gain access to tools that let you explore…

Event streaming with Kafka Streams is powerful but can feel overwhelming to understand and implement. Breaking down ​​advanced concepts into smaller single-purpose topologies makes learning more approachable. Kafka Streams concepts will be introduced with an interactive web application that allows you to visualize input topics, output topics, changelog topics, state stores, and more. What happens when state store caching is disabled? What if topology optimization is enabled? Or what if stream time isn't advanced? These questions will be easily explored by visualizing the topology and Kafka Streams configurations. This interactive tutorial's real-time events are generated by actual data on your laptop, including running processes, thread details, windows, services, and user sessions. Moving a window on your laptop can trigger many examples, allowing you to see how the topology handles them. The audience will select from an interactive poll of concepts to cover for the session, selecting from concepts on branching, emitting on change, windowing, repartitioning, joining, and more. Join me on this ​​journey of learning Kafka Streams. You'll deepen your understanding of Kafka Streams…