The Apache Kafka community is pleased to announce the release for
Apache Kafka 4.2.0
This release has many exciting changes:
* Kafka Queues (Share Groups) is now production-ready with new
features like the RENEW acknowledgement type for extended processing
times, adaptive batching for share coordinators, soft and strict
enforcements of quantity of fetched records, and comprehensive lag
metrics.
* Kafka Streams brings the server-side rebalance protocol to GA with a
limited feature set, adds dead letter queue support in exception
handlers, introduces anchored wall-clock punctuation for deterministic
scheduling, and gives users full control over whether to send a leave
group request on closing.
* This release also delivers significant improvements to consistency
and observability: CLI tools now feature standardized arguments like
–bootstrap-server across all tools, metric naming has been corrected
to follow the kafka.COMPONENT convention, and new idle ratio metrics
provide better visibility into controller and MetadataLoader
performance.
* Security is enhanced with a new allowlist connector client
configuration override policy, while thread-safety improvements to
RecordHeader eliminate concurrency risks.
* Additional highlights include external schema support in
JsonConverter for reduced message sizes, dynamic configuration for
remote log manager thread pools, adaptive batching in group
coordinators, and rack ID exposure in the Admin API for consumer and
share group members.
All of the changes in this release can be found in the release notes:
https://www.apache.org/dist/kafka/4.2.0/RELEASE_NOTES.html
An overview of the release can be found in our announcement blog post:
https://kafka.apache.org/blog
You can download the source and binary release (Scala 2.13) from:
https://kafka.apache.org/downloads#4.2.0
---------------------------------------------------------------------------------------------------
Apache Kafka is a distributed streaming platform with four core APIs:
** The Producer API allows an application to publish a stream of 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 155 contributors to this release!
(Please report an unintended omission)
Abhi Tiwari, Abhijeet Kumar, Abhinav Dixit, Abhiram98, Alex, Alieh
Saeedi, ally heev, Alyssa Huang, Andrew J Schofield, Anton Vasanth,
Apoorv Mittal, Arpit Goyal, Artem Livshits, Bill Bejeck, Bolin Lin,
Bruno Cadonna, Calvin Liu, Chang-Chi Hsu, Chang-Yu Huang, Chia-Ping
Tsai, Chih-Yuan Chien, Chirag Wadhwa, Chris Egerton, Christo Lolov,
Chuckame, Clemens Hutter, Colin Patrick McCabe, d00791190, Dave
Troiano, David Arthur, David Jacot, Deep Golani, Dejan Stojadinović,
devtrace404, Dmitry Werner, Dongnuo Lyu, Donny Nadolny, Eduwer
Camacaro, Elizabeth Bennett, EME, Eric Chang, Erik Anderson, Evan
Zhou, Evgeniy Kuvardin, farzan ghalami, Fatih, Federico Valeri,
Gantigmaa Selenge, Gasparina Damien, Gaurav Narula, Genseric Ghiro,
George Wu, Greg Harris, Harish Vishwanath, Herman Kolstad Jakobsen,
Hong-Yi Chen, Ismael Juma, Izzy Harker, Jared Harley, Jhen-Yung Hsu,
Jian, Jim Galasyn, Jimmy Wang, Jing-Jia Hung, Jinhe Zhang, Joel
Hamill, Jonah Hooper, Josep Prat, José Armando García Sancio, Juha
Mynttinen, Jun Rao, Justine Olshan, k-apol, Kamal Chandraprakash,
Kaushik Raina, keemsisi, Ken Huang, Kevin Wu, Kirk True, knoxy5467,
KTKTK-HZ, Kuan-Po Tseng, Lan Ding, Levani Kokhreidze, Liam
Clarke-Hutchinson, Lianet Magrans, Linsiyuan9, Logan Zhu, lorcan, Lord
of Abyss, Lucas Brutschy, Lucy Liu, Luke Chen, Mahsa Seifikar,
majialong, Manikumar Reddy, Maros Orsak, Masahiro Mori, Mason Chen,
Matt Welch, Matthias J. Sax, Michael Knox, Michael Morris, Mickael
Maison, Ming-Yen Chung, NeatGuyCoding, Nick Guo, NICOLAS GUYOMAR,
Nikita Shupletsov, Now, Okada Haruki, Omnia Ibrahim, Otmar Ertl, OuO,
Paolo Patierno, Patrik Nagy, Pawel Szymczyk, PoAn Yang, Ken Huang,
Priyanka K U, Rajani K, Rajini Sivaram, Ram, Ritika Reddy, Robert
Young, Ryan Dielhenn, S.Y. Wang, samarth-ksolves, Sanskar Jhajharia,
Satish Duggana, Sean Quah, Sebastien Viale, Shang-Hao Yang, Shashank,
Shivsundar R, Siyang He, Sophie Blee-Goldman, Stig Døssing, stroller,
Sushant Mahajan, TaiJuWu, TengYao Chi, Tsung-Han Ho (Miles Ho),
Ubuntu, Uladzislau Blok, Vincent PÉRICART, Xiao Yang, xijiu,
Xuan-Zhang Gong, yangxuze, Yeikel Santana, Yu-Syuan Jheng, YuChia Ma,
Yunchi Pang, Yung
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,
Christo
Release Manager for Apache Kafka 4.2.0
Apache Kafka 4.2.0
This release has many exciting changes:
* Kafka Queues (Share Groups) is now production-ready with new
features like the RENEW acknowledgement type for extended processing
times, adaptive batching for share coordinators, soft and strict
enforcements of quantity of fetched records, and comprehensive lag
metrics.
* Kafka Streams brings the server-side rebalance protocol to GA with a
limited feature set, adds dead letter queue support in exception
handlers, introduces anchored wall-clock punctuation for deterministic
scheduling, and gives users full control over whether to send a leave
group request on closing.
* This release also delivers significant improvements to consistency
and observability: CLI tools now feature standardized arguments like
–bootstrap-server across all tools, metric naming has been corrected
to follow the kafka.COMPONENT convention, and new idle ratio metrics
provide better visibility into controller and MetadataLoader
performance.
* Security is enhanced with a new allowlist connector client
configuration override policy, while thread-safety improvements to
RecordHeader eliminate concurrency risks.
* Additional highlights include external schema support in
JsonConverter for reduced message sizes, dynamic configuration for
remote log manager thread pools, adaptive batching in group
coordinators, and rack ID exposure in the Admin API for consumer and
share group members.
All of the changes in this release can be found in the release notes:
https://www.apache.org/dist/kafka/4.2.0/RELEASE_NOTES.html
An overview of the release can be found in our announcement blog post:
https://kafka.apache.org/blog
You can download the source and binary release (Scala 2.13) from:
https://kafka.apache.org/downloads#4.2.0
---------------------------------------------------------------------------------------------------
Apache Kafka is a distributed streaming platform with four core APIs:
** The Producer API allows an application to publish a stream of 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 155 contributors to this release!
(Please report an unintended omission)
Abhi Tiwari, Abhijeet Kumar, Abhinav Dixit, Abhiram98, Alex, Alieh
Saeedi, ally heev, Alyssa Huang, Andrew J Schofield, Anton Vasanth,
Apoorv Mittal, Arpit Goyal, Artem Livshits, Bill Bejeck, Bolin Lin,
Bruno Cadonna, Calvin Liu, Chang-Chi Hsu, Chang-Yu Huang, Chia-Ping
Tsai, Chih-Yuan Chien, Chirag Wadhwa, Chris Egerton, Christo Lolov,
Chuckame, Clemens Hutter, Colin Patrick McCabe, d00791190, Dave
Troiano, David Arthur, David Jacot, Deep Golani, Dejan Stojadinović,
devtrace404, Dmitry Werner, Dongnuo Lyu, Donny Nadolny, Eduwer
Camacaro, Elizabeth Bennett, EME, Eric Chang, Erik Anderson, Evan
Zhou, Evgeniy Kuvardin, farzan ghalami, Fatih, Federico Valeri,
Gantigmaa Selenge, Gasparina Damien, Gaurav Narula, Genseric Ghiro,
George Wu, Greg Harris, Harish Vishwanath, Herman Kolstad Jakobsen,
Hong-Yi Chen, Ismael Juma, Izzy Harker, Jared Harley, Jhen-Yung Hsu,
Jian, Jim Galasyn, Jimmy Wang, Jing-Jia Hung, Jinhe Zhang, Joel
Hamill, Jonah Hooper, Josep Prat, José Armando García Sancio, Juha
Mynttinen, Jun Rao, Justine Olshan, k-apol, Kamal Chandraprakash,
Kaushik Raina, keemsisi, Ken Huang, Kevin Wu, Kirk True, knoxy5467,
KTKTK-HZ, Kuan-Po Tseng, Lan Ding, Levani Kokhreidze, Liam
Clarke-Hutchinson, Lianet Magrans, Linsiyuan9, Logan Zhu, lorcan, Lord
of Abyss, Lucas Brutschy, Lucy Liu, Luke Chen, Mahsa Seifikar,
majialong, Manikumar Reddy, Maros Orsak, Masahiro Mori, Mason Chen,
Matt Welch, Matthias J. Sax, Michael Knox, Michael Morris, Mickael
Maison, Ming-Yen Chung, NeatGuyCoding, Nick Guo, NICOLAS GUYOMAR,
Nikita Shupletsov, Now, Okada Haruki, Omnia Ibrahim, Otmar Ertl, OuO,
Paolo Patierno, Patrik Nagy, Pawel Szymczyk, PoAn Yang, Ken Huang,
Priyanka K U, Rajani K, Rajini Sivaram, Ram, Ritika Reddy, Robert
Young, Ryan Dielhenn, S.Y. Wang, samarth-ksolves, Sanskar Jhajharia,
Satish Duggana, Sean Quah, Sebastien Viale, Shang-Hao Yang, Shashank,
Shivsundar R, Siyang He, Sophie Blee-Goldman, Stig Døssing, stroller,
Sushant Mahajan, TaiJuWu, TengYao Chi, Tsung-Han Ho (Miles Ho),
Ubuntu, Uladzislau Blok, Vincent PÉRICART, Xiao Yang, xijiu,
Xuan-Zhang Gong, yangxuze, Yeikel Santana, Yu-Syuan Jheng, YuChia Ma,
Yunchi Pang, Yung
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,
Christo
Release Manager for Apache Kafka 4.2.0
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