The Apache Kafka community is pleased to announce the release for Apache Kafka 2.7.0
* Configurable TCP connection timeout and improve the initial metadata fetch * Enforce broker-wide and per-listener connection creation rate (KIP-612, part 1) * Throttle Create Topic, Create Partition and Delete Topic Operations * Add TRACE-level end-to-end latency metrics to Streams * Add Broker-side SCRAM Config API * Support PEM format for SSL certificates and private key * Add RocksDB Memory Consumption to RocksDB Metrics * Add Sliding-Window support for Aggregations This release also includes a few other features, 53 improvements, and 91 bug fixes. All of the changes in this release can be found in the release notes: https://www.apache.org/dist/kafka/2.7.0/RELEASE_NOTES.html You can read about some of the more prominent changes in the Apache Kafka blog: https://blogs.apache.org/kafka/entry/what-s-new-in-apache4 You can download the source and binary release (Scala 2.12, 2.13) from: https://kafka.apache.org/downloads#2.7.0 --------------------------------------------------------------------------------------------------- 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 117 contributors to this release! A. Sophie Blee-Goldman, Aakash Shah, Adam Bellemare, Adem Efe Gencer, albert02lowis, Alex Diachenko, Andras Katona, Andre Araujo, Andrew Choi, Andrew Egelhofer, Andy Coates, Ankit Kumar, Anna Povzner, Antony Stubbs, Arjun Satish, Ashish Roy, Auston, Badai Aqrandista, Benoit Maggi, bill, Bill Bejeck, Bob Barrett, Boyang Chen, Brian Byrne, Bruno Cadonna, Can Cecen, Cheng Tan, Chia-Ping Tsai, Chris Egerton, Colin Patrick McCabe, David Arthur, David Jacot, David Mao, Dhruvil Shah, Dima Reznik, Edoardo Comar, Ego, Evelyn Bayes, feyman2016, Gal Margalit, gnkoshelev, Gokul Srinivas, Gonzalo Muñoz, Greg Harris, Guozhang Wang, high.lee, huangyiming, huxi, Igor Soarez, Ismael Juma, Ivan Yurchenko, Jason Gustafson, Jeff Kim, jeff kim, Jesse Gorzinski, jiameixie, Jim Galasyn, JoelWee, John Roesler, John Thomas, Jorge Esteban Quilcate Otoya, Julien Jean Paul Sirocchi, Justine Olshan, khairy, Konstantine Karantasis, Kowshik Prakasam, leah, Lee Dongjin, Leonard Ge, Levani Kokhreidze, Lucas Bradstreet, Lucent-Wong, Luke Chen, Mandar Tillu, manijndl7, Manikumar Reddy, Mario Molina, Matthias J. Sax, Micah Paul Ramos, Michael Bingham, Mickael Maison, Navina Ramesh, Nikhil Bhatia, Nikolay, Nikolay Izhikov, Ning Zhang, Nitesh Mor, Noa Resare, Rajini Sivaram, Raman Verma, Randall Hauch, Rens Groothuijsen, Richard Fussenegger, Rob Meng, Rohan, Ron Dagostino, Sanjana Kaundinya, Sasaki Toru, sbellapu, serjchebotarev, Shaik Zakir Hussain, Shailesh Panwar, Sharath Bhat, showuon, Stanislav Kozlovski, Thorsten Hake, Tom Bentley, tswstarplanet, vamossagar12, Vikas Singh, vinoth chandar, Vito Jeng, voffcheg109, xakassi, Xavier Léauté, Yuriy Badalyantc, Zach Zhang 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, Bill Bejeck
