Apache Kafka® is an open source event streaming platform that provides a framework for storing, reading, and analyzing data streams at scale. Used by more than 30% of the Fortune 500, today, Kafka is used for countless use cases, from high-performance data pipelines and streaming analytics, to application integration, and IoT solutions.
There are numerous features of Kafka that make it the de facto standard for real-time data stream processing. Gaining a deeper understanding of just a handful of these features can enable you to quickly improve the performance of your applications, the efficiency of your development process, and use Kafka to its fullest potential, no matter your use case.
In this white paper, you’ll learn about five Kafka elements that deserve closer attention, either because they significantly improve upon the behavior of their predecessors, because they are easy to overlook or to make assumptions about, or simply because they are extremely useful.
Bill Bejeck is working at Confluent as an integration architect on the Developer Relations team. He was a software engineer for over 15 years and has regularly contributed to Kafka Streams. Before Confluent, he worked on various ingest applications as a U.S. Government contractor using distributed software such as Apache Kafka, Spark, and Hadoop. He has also written a book about Kafka Streams titled Kafka Streams in Action.