The Apache Kafka community is pleased to announce the release for Apache Kafka 2.4.0
This release includes many new features, including: - Allow consumers to fetch from closest replica - Support for incremental cooperative rebalancing to the consumer rebalance protocol - MirrorMaker 2.0 (MM2), a new multi-cluster, cross-datacenter replication engine - New Java authorizer Interface - Support for non-key joining in KTable - Administrative API for replica reassignment - Securing Internal connect REST endpoints - API to delete consumer offsets and expose it via the AdminClient. All of the changes in this release can be found in the release notes: https://www.apache.org/dist/kafka/2.4.0/RELEASE_NOTES.html You can download the source and binary release (Scala 2.11, 2.12 and 2.13) from: https://kafka.apache.org/downloads#2.4.0 --------------------------------------------------------------------------------------------------- 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 121 contributors to this release! A. Sophie Blee-Goldman, Adam Bellemare, Alex Diachenko, Alex Leung, Alex Mironov, Alice, Almog Gavra, Anastasia Vela, anatasiavela, Andy Coates, Antony Stubbs, Arjun Satish, Arlo Louis O'Keeffe, Arvind Thirunarayanan, asutosh936, Bill Bejeck, Bob Barrett, Boyang Chen, Brian Bushree, Bruno Cadonna, cadonna, Carlos Manuel Duclos Vergara, Cheng Pan, Chia-Ping Tsai, Chris Egerton, Chris Pettitt, Chris Stromberger, Colin Hicks, Colin P. Mccabe, Colin Patrick McCabe, cpettitt-confluent, cwildman, Cyrus Vafadari, David Arthur, David Jacot, Dejan Stojadinović, Dhruvil Shah, Florian Hussonnois, Gardner Vickers, Gemma Singleton, Grant Henke, Greg Harris, Gunnar Morling, Guozhang Wang, Gwen Shapira, Hai-Dang Dam, highluck, huxi, Igor Soarez, Ismael Juma, James Cheng, Jason Gustafson, Jeff Huang, Joel Hamill, John Roesler, jolshan, José Armando García Sancio, Jukka Karvanen, Justine Olshan, Kamal Chandraprakash, Karan Kumar, Kengo Seki, Kevin Lu, khairy, Konstantine Karantasis, Lee Dongjin, Lifei Chen, Lucas Bradstreet, LuyingLiu, Magesh Nandakumar, Manikumar Reddy, Matthias J. Sax, Michał Borowiecki, Michał Siatkowski, Mickael Maison, mjarvie, mmanna-sapfgl, Nacho Muñoz Gómez, Nathan Murthy, Nigel Liang, NIkhil Bhatia, Nikolay, Omar Al-Safi, Omkar Mestry, Paul, pkleindl, Rajan Chauhan, Rajini Sivaram, Randall Hauch, Richard Yu, Robert Yokota, Rohan, Ron Dagostino, Ryanne Dolan, saisandeep, Scott Hendricks, sdreynolds, Sean Glover, Sergey Prokofiev, slim, soondenana, Stanislav Kozlovski, Stanislav Vodetskyi, SuryaTeja Duggi, tadsul, teebee, Tirtha Chatterjee, Tu Tran, Tu V. Tran, Vahid Hashemian, Victoria Bialas, Vikas Singh, Viktor Somogyi, Viktor Somogyi-Vass, vinoth chandar, wenhoujx, Wennn, Will James, wineandcheeze, Yaroslav Tkachenko, 康智冬 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, Manikumar
