I am very excited to announce the availability of the 0.10 release of Apache Kafka and the 3.0 release of the Confluent Platform. This release marks the availability of Kafka Streams, a simple solution to stream processing and Confluent Control Center, the first comprehensive management and monitoring system for Apache Kafka. Around 112 contributors provided bug fixes, improvements, and new features such that in total 413 JIRA issues and 13 KIPs were resolved.
For organizations that want to build a streaming data pipeline around Apache Kafka, Confluent Platform is the easiest way to get started. As the creators of Apache Kafka, we learned from our own and others’ experiences as some of the largest companies in the world transitioned to a central stream data platform and have assembled an open-source, well-tested and fully supported platform of extensions on Kafka that make it more capable and easier to deploy and operate.
Confluent Platform is open-source and includes the latest version of Apache Kafka with critical bug fixes, as well as a set of open-source extensions that help you get started with Kafka:
The 3.0 release of Confluent Platform introduces the first commercial product through the Confluent Platform Enterprise offering— Control Center. It is a web-based tool for comprehensive management and monitoring of Apache Kafka. In version 3.0.0, Control Center offers two essential components of building streaming data pipelines:
Apache Kafka 0.10.0.0 is a major release of Apache Kafka and includes a number of new features and enhancements. Highlights include:
max.poll.recordsthat allows developers to limit the number of messages returned.
The Kafka community has actively participated in shipping this release. According to git shortlog, 112 people contributed to this release. Thank you for your contributions!
Adam Kunicki, Aditya Auradkar, Alex Loddengaard, Alex Sherwin, Allen Wang, Andrea Cosentino, Anna Povzner, Ashish Singh, Atul Soman, Ben Stopford, Bill Bejeck, BINLEI XUE, Chen Shangan, Chen Zhu, Christian Posta, Cory Kolbeck, Damian Guy, dan norwood, Dana Powers, David Jacot, Denise Fernandez, Dionysis Grigoropoulos, Dmitry Stratiychuk, Dong Lin, Dongjoon Hyun, Drausin Wulsin, Duncan Sands, Dustin Cote, Eamon Zhang, edoardo, Edward Ribeiro, Eno Thereska, Ewen Cheslack-Postava, Flavio Junqueira, Francois Visconte, Frank Scholten, Gabriel Zhang, gaob13, Geoff Anderson, glikson, Grant Henke, Greg Fodor, Guozhang Wang, Gwen Shapira, Igor Stepanov, Ishita Mandhan, Ismael Juma, Jaikiran Pai, Jakub Nowak, James Cheng, Jason Gustafson, Jay Kreps, Jeff Klukas, Jeremy Custenborder, Jesse Anderson, jholoman, Jiangjie Qin, Jin Xing, jinxing, Jonathan Bond, Jun Rao, Ján Koščo, Kaufman Ng, kenji yoshida, Kim Christensen, Kishore Senji, Konrad, Liquan Pei, Luciano Afranllie, Magnus Edenhill, Maksim Logvinenko, manasvigupta, Manikumar reddy O, Mark Grover, Matt Fluet, Matt McClure, Matthias J. Sax, Mayuresh Gharat, Micah Zoltu, Michael Blume, Michael G. Noll, Mickael Maison, Onur Karaman, ouyangliduo, Parth Brahmbhatt, Paul Cavallaro, Pierre-Yves Ritschard, Piotr Szwed, Praveen Devarao, Rafael Winterhalter, Rajini Sivaram, Randall Hauch, Richard Whaling, Ryan P, Samuel Julius Hecht, Sasaki Toru, Som Sahu, Sriharsha Chintalapani, Stig Rohde Døssing, Tao Xiao, Tom Crayford, Tom Dearman, Tom Graves, Tom Lee, Tomasz Nurkiewicz, Vahid Hashemian, William Thurston, Xin Wang, Yasuhiro Matsuda, Yifan Ying, Yuto Kawamura, zhuchen1018
Camus in Confluent Platform is deprecated in Confluent Platform 3.0 and may be removed in a release after Confluent Platform 3.1. To export data from Kafka to HDFS and Hive, we recommend Kafka Connect with the Confluent HDFS connector as an alternative.
In the forthcoming releases, the Apache Kafka community plans to focus on operational simplicity and stronger delivery guarantees. This work includes improved data balancing, more security enhancements, and support for exactly-once delivery in Apache Kafka. Confluent Platform will have more clients, connectors and extended monitoring and management capabilities in the Control Center.
If you enjoy working on Kafka and would like to do so full time, we are hiring at Confluent!
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