Listen to Tim Berglund, Gwen Shapira, and guests unpack a variety of topics surrounding Apache Kafka®, Confluent, real-time data streaming, and the cloud.
Viktor Gamov (Developer Advocate, Confluent) returns to Streaming Audio to explain the magic of ksqlDB, ideal testing environments for ksqlDB, and the ksqlDB test runner. He also talks about the future of ksqlDB, the future of integration testing, and his favorite new feature among recent upgrades.
Learn about the five different parts to a business value framework: (1) baseline, (2) target state, (3) quantified benefits, (4) unquantified benefits, and (5) proof points; cost effectiveness with Confluent Cloud; how to measure ROI vs. TCO; and a retail example from a customer that details their implementation of an event streaming platform.
Inventory management systems are crucial for reducing real-time inventory data drift, improving customer experience, and minimizing out-of-stock events. Kafka provides seamless inventory tracking at scale, saving billions of dollars in the supply chain, making modernized data architectures more important to retailers now more than ever. In this episode, we’ll discuss how Kafka enables stateful event streaming on a cloud-native platform for application and architecture modernization, leveraging Spring Boot, Kafka Streams, and Apache Cassandra.
Apache Kafka® Committer Matthias J. Sax explains fault tolerance, high-availability stream processing, and Kafka Streams. He explains the differences between changelogging and checkpointing, as well as making changes in Kafka versus hot standbys, explaining what qualifies nodes as a hot standby, why Kafka Streams doesn’t do watermarking, and finally, why Kafka Streams is a library and not infrastructure.
The five components of latency are produce time, publish time, commit time, catch-up time, and fetch time. When consumer pulling adds to latency, Anna Povzner shares some best practices to keep in mind for how to think about partitioning in conjunction with latency. She also discusses client configuration in the cloud, interesting problems she's helped solve for customers, and her top two tips for debugging latency.
Tim Berglund is a teacher, author, and technology leader with Confluent, where he serves as the senior director of developer advocacy. He can frequently be found at speaking at conferences in the U.S. and all over the world. Tim is the co-presenter of various O'Reilly training videos on topics ranging from Git to distributed systems, and he is the author of "Gradle Beyond the Basics." He lives in Littleton, CO, U.S., with the wife of his youth.
Gwen Shapira is an engineering leader at Confluent. She has over 15 years of experience working with code and customers to build scalable data architectures, integrating relational and big data technologies. Gwen is the author of "Kafka: The Definitive Guide" and "Hadoop Application Architectures." Gwen is a frequent presenter at industry conferences, a PMC member on the Apache Kafka project, and a committer on Apache Sqoop™. When Gwen isn't building data pipelines or thinking up new features, you can find her pedaling on her bike exploring the roads and trails of California, and beyond.
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