Meet your new host of the Streaming Audio podcast: Kris Jenkins (Senior Developer Advocate, Confluent)! In this preview, Kris shares a few highlights from forthcoming episodes to look forward to, spanning topics from data mesh, cloud-native technologies, and serverless Apache Kafka, to data modeling.

After nearly 200 podcast episodes of Streaming Audio, Tim Berglund bids farewell in his last episode as host of the show. Tim reflects on the many great memories with guests who have appeared on the segment—and each for its own reasons. He has covered a wide variety of topics, ranging from Apache Kafka fundamentals, microservices, event stream processing, use cases, to cloud-native Kafka, data mesh, and more.

What is event sourcing, and how does it work? Event sourcing is often used interchangeably with event-driven architecture and event stream processing. However, Anna McDonald (Principal Customer Success Technical Architect, Confluent) explains it's a specific category of its own—an event streaming pattern.

In an effort to make Apache Kafka cloud native, Anna Povzener (Principal Engineer, Confluent) and Anastasia Vela (Software Engineer I, Confluent) have been working to expand multi-tenancy to cloud-native systems with automated capacity planning and scaling in Confluent Cloud. They explain how cloud-native data systems are different from legacy databases and share the technical requirements needed to create multi-tenancy for managed Kafka as a service.

Apache Kafka 3.1 is here with exciting new features and improvements! On behalf of the Kafka community, Danica Fine (Senior Developer Advocate, Confluent) shares release highlights that you won’t want to miss, including foreign-key joins in Kafka Streams and improvements that will provide consistency for Kafka latency metrics.