The Apache Kafka community is pleased to announce the release for Apache Kafka 3.4.1.
This is a bug fix release and it includes fixes and improvements from 58 JIRAs, including a few critical bugs: - core KAFKA-14644 Process should stop after failure in raft IO thread KAFKA-14946 KRaft controller node shutting down while renouncing leadership KAFKA-14887 ZK session timeout can cause broker to shutdown - client KAFKA-14639 Kafka CooperativeStickyAssignor revokes/assigns partition in one rebalance cycle - connect KAFKA-12558 MM2 may not sync partition offsets correctly KAFKA-14666 MM2 should translate consumer group offsets behind replication flow - stream KAFKA-14172 bug: State stores lose state when tasks are reassigned under EOS All of the changes in this release can be found in the release notes: https://www.apache.org/dist/kafka/3.4.1/RELEASE_NOTES.html You can download the source and binary release (Scala 2.12 and Scala 2.13) from: https://kafka.apache.org/downloads#3.4.1 --------------------------------------------------------------------------------------------------- Apache Kafka is a distributed streaming platform with four core APIs: ** The Producer API allows an application to publish a stream records to one or more Kafka topics. ** The Consumer API allows an application to subscribe to one or more topics and process the stream of records produced to them. ** The Streams API allows an application to act as a stream processor, consuming an input stream from one or more topics and producing an output stream to one or more output topics, effectively transforming the input streams to output streams. ** The Connector API allows building and running reusable producers or consumers that connect Kafka topics to existing applications or data systems. For example, a connector to a relational database might capture every change to a table. With these APIs, Kafka can be used for two broad classes of application: ** Building real-time streaming data pipelines that reliably get data between systems or applications. ** Building real-time streaming applications that transform or react to the streams of data. Apache Kafka is in use at large and small companies worldwide, including Capital One, Goldman Sachs, ING, LinkedIn, Netflix, Pinterest, Rabobank, Target, The New York Times, Uber, Yelp, and Zalando, among others. A big thank you for the following 32 contributors to this release! atu-sharm, Chia-Ping Tsai, Chris Egerton, Colin Patrick McCabe, csolidum, David Arthur, David Jacot, Divij Vaidya, egyedt, emilnkrastev, Eric Haag, Greg Harris, Guozhang Wang, Hector Geraldino, hudeqi, Jason Gustafson, Jeff Kim, Jorge Esteban Quilcate Otoya, José Armando García Sancio, Lucia Cerchie, Luke Chen, Manikumar Reddy, Matthias J. Sax, Mickael Maison, Philip Nee, Purshotam Chauhan, Rajini Sivaram, Ron Dagostino, Terry, Victoria Xia, Viktor Somogyi-Vass, Yash Mayya We welcome your help and feedback. For more information on how to report problems, and to get involved, visit the project website at https://kafka.apache.org/ Thank you! Regards, Luke
