Listen to Tim Berglund, Gwen Shapira, and guests unpack a variety of topics surrounding Apache Kafka®, Confluent, real-time data streaming, and the cloud.
Matthias J. Sax is back to discuss how event streaming has changed the game, making time management more simple yet efficient. He explains what watermarking is, the reasons behind why Kafka Streams doesn’t use them, and an alternative approach to watermarking informally called the “slack time approach.”
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.
There are two primary industries within the Internet of Things (IoT): industrial IoT (IIoT) and consumer IoT (CIoT), both of which can benefit from the Kafka ecosystem, including Kafka Streams and Kafka Connect.. Kai Waehner shares example use cases where he’s seen IoT integration in action, specifically focusing on Walmart and its real-time customer integration using the Walmart app.
There’s something about YAML and the word “Docker” that doesn’t sit well with Viktor Gamov (Developer Advocate, Confluent), but Kafka Streams on Kubernetes is a phrase that does. Viktor describes what that process looks like and how Jib helps build, test, and deploy Kafka Streams applications on Kubernetes for an improved DevOps experience.
Neil Buesing (Director of Real-Time Data, Object Partners) discusses what a day in his life looks like and how Kafka Streams helps analyze flight data.
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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