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Streaming Audio Podcast

Listen to Tim Berglund and guests unpack a variety of topics surrounding Apache Kafka®, Confluent, real-time data streaming, and the cloud.

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Episode 113August 6, 2020 | 10 min

Apache Kafka 2.6 - Overview of Latest Features, Updates, and KIPs

Apache Kafka 2.6 is out! This release includes progress toward adding client quota APIs to the admin client, exposing disk read and write metrics, and support for Java 14, in addition to Kafka Connect and Kafka Streams updates.

Episode 112August 3, 2020 | 39 min

Testing ksqlDB Applications ft. Viktor Gamov

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.

Episode 111July 27, 2020 | 54 min

How to Measure the Business Value of Confluent Cloud ft. Lyndon Hedderly

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.

Episode 110July 20, 2020 | 41 min

Modernizing Inventory Management Technology ft. Sina Sojoodi and Rohit Kelapure

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.

Episode 109July 15, 2020 | 54 min

Fault Tolerance and High Availability in Kafka Streams and ksqlDB ft. Matthias J. Sax

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.

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Meet your host

Tim Berglund

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.

Got questions?

If there's something you want to know about Apache Kafka, Confluent or event streaming, please send us an email with your question and we'll hope to answer it on the next episode of Ask Confluent.

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