Thank you for your great works! Thanks again for the commiters and all the contributors!
On Tue, Jul 31, 2018 at 1:05 AM Ismael Juma <isma...@gmail.com> wrote: > Thanks to everyone who contributed to the release (including testing and > bug reports)! And thank you Rajini for managing the release. > > Ismael > > On Mon, 30 Jul 2018, 03:25 Rajini Sivaram, <rsiva...@apache.org> wrote: > > > The Apache Kafka community is pleased to announce the release for > > > > Apache Kafka 2.0.0. > > > > > > > > > > > > This is a major release and includes significant new features from > > > > 40 KIPs. It contains fixes and improvements from 246 JIRAs, including > > > > a few critical bugs. Here is a summary of some notable changes: > > > > ** KIP-290 adds support for prefixed ACLs, simplifying access control > > management in large secure deployments. Bulk access to topics, > > consumer groups or transactional ids with a prefix can now be granted > > using a single rule. Access control for topic creation has also been > > improved to enable access to be granted to create specific topics or > > topics with a prefix. > > > > ** KIP-255 adds a framework for authenticating to Kafka brokers using > > OAuth2 bearer tokens. The SASL/OAUTHBEARER implementation is > > customizable using callbacks for token retrieval and validation. > > > > **Host name verification is now enabled by default for SSL connections > > to ensure that the default SSL configuration is not susceptible to > > man-in-the middle attacks. You can disable this verification for > > deployments where validation is performed using other mechanisms. > > > > ** You can now dynamically update SSL trust stores without broker > restart. > > You can also configure security for broker listeners in ZooKeeper before > > starting brokers, including SSL key store and trust store passwords and > > JAAS configuration for SASL. With this new feature, you can store > sensitive > > password configs in encrypted form in ZooKeeper rather than in cleartext > > in the broker properties file. > > > > ** The replication protocol has been improved to avoid log divergence > > between leader and follower during fast leader failover. We have also > > improved resilience of brokers by reducing the memory footprint of > > message down-conversions. By using message chunking, both memory > > usage and memory reference time have been reduced to avoid > > OutOfMemory errors in brokers. > > > > ** Kafka clients are now notified of throttling before any throttling is > > applied > > when quotas are enabled. This enables clients to distinguish between > > network errors and large throttle times when quotas are exceeded. > > > > ** We have added a configuration option for Kafka consumer to avoid > > indefinite blocking in the consumer. > > > > ** We have dropped support for Java 7 and removed the previously > > deprecated Scala producer and consumer. > > > > ** Kafka Connect includes a number of improvements and features. > > KIP-298 enables you to control how errors in connectors, transformations > > and converters are handled by enabling automatic retries and controlling > > the > > number of errors that are tolerated before the connector is stopped. More > > contextual information can be included in the logs to help diagnose > > problems > > and problematic messages consumed by sink connectors can be sent to a > > dead letter queue rather than forcing the connector to stop. > > > > ** KIP-297 adds a new extension point to move secrets out of connector > > configurations and integrate with any external key management system. > > The placeholders in connector configurations are only resolved before > > sending the configuration to the connector, ensuring that secrets are > > stored > > and managed securely in your preferred key management system and > > not exposed over the REST APIs or in log files. > > > > ** We have added a thin Scala wrapper API for our Kafka Streams DSL, > > which provides better type inference and better type safety during > compile > > time. Scala users can have less boilerplate in their code, notably > > regarding > > Serdes with new implicit Serdes. > > > > ** Message headers are now supported in the Kafka Streams Processor API, > > allowing users to add and manipulate headers read from the source topics > > and propagate them to the sink topics. > > > > ** Windowed aggregations performance in Kafka Streams has been largely > > improved (sometimes by an order of magnitude) thanks to the new > > single-key-fetch API. > > > > ** We have further improved unit testibility of Kafka Streams with the > > kafka-streams-testutil artifact. > > > > > > > > > > > > All of the changes in this release can be found in the release notes: > > > > https://www.apache.org/dist/kafka/2.0.0/RELEASE_NOTES.html > > > > > > > > > > > > You can download the source and binary release (Scala 2.11 and Scala > 2.12) > > from: > > > > https://kafka.apache.org/downloads#2.0.0 > > <https://kafka.apache.org/downloads#2.0.0> > > > > > > > > > > > --------------------------------------------------------------------------------------------------- > > > > > > > > > > > > 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 131 contributors to this release! > > > > > > > > Adem Efe Gencer, Alex D, Alex Dunayevsky, Allen Wang, Andras Beni, > > > > Andy Bryant, Andy Coates, Anna Povzner, Arjun Satish, asutosh936, > > > > Attila Sasvari, bartdevylder, Benedict Jin, Bill Bejeck, Blake Miller, > > > > Boyang Chen, cburroughs, Chia-Ping Tsai, Chris Egerton, Colin P. Mccabe, > > > > Colin Patrick McCabe, ConcurrencyPractitioner, Damian Guy, dan norwood, > > > > Daniel Shuy, Daniel Wojda, Dark, David Glasser, Debasish Ghosh, Detharon, > > > > Dhruvil Shah, Dmitry Minkovsky, Dong Lin, Edoardo Comar, emmanuel Harel, > > > > Eugene Sevastyanov, Ewen Cheslack-Postava, Fedor Bobin, > fedosov-alexander, > > > > Filipe Agapito, Florian Hussonnois, fredfp, Gilles Degols, gitlw, > Gitomain, > > > > Guangxian, Gunju Ko, Gunnar Morling, Guozhang Wang, hmcl, huxi, huxihx, > > > > Igor Kostiakov, Ismael Juma, Jacek Laskowski, Jagadesh Adireddi, > > > > Jarek Rudzinski, Jason Gustafson, Jeff Klukas, Jeremy Custenborder, > > > > Jiangjie (Becket) Qin, Jiangjie Qin, JieFang.He, Jimin Hsieh, Joan > Goyeau, > > > > Joel Hamill, John Roesler, Jon Lee, Jorge Quilcate Otoya, Jun Rao, > > > > Kamal C, khairy, Koen De Groote, Konstantine Karantasis, Lee Dongjin, > > > > Liju John, Liquan Pei, lisa2lisa, Lucas Wang, Magesh Nandakumar, > > > > Magnus Edenhill, Magnus Reftel, Manikumar Reddy, Manikumar Reddy O, > > > > manjuapu, Mats Julian Olsen, Matthias J. Sax, Max Zheng, maytals, > > > > Michael Arndt, Michael G. Noll, Mickael Maison, nafshartous, Nick > Travers, > > > > nixsticks, Paolo Patierno, parafiend, Patrik Erdes, Radai Rosenblatt, > > > > Rajini Sivaram, Randall Hauch, ro7m, Robert Yokota, Roman Khlebnov, > > > > Ron Dagostino, Sandor Murakozi, Sasaki Toru, Sean Glover, > > > > Sebastian Bauersfeld, Siva Santhalingam, Stanislav Kozlovski, Stephane > > Maarek, > > > > Stuart Perks, Surabhi Dixit, Sönke Liebau, taekyung, tedyu, Thomas > Leplus, > > > > UVN, Vahid Hashemian, Valentino Proietti, Viktor Somogyi, Vitaly Pushkar, > > > > Wladimir Schmidt, wushujames, Xavier Léauté, xin, yaphet, > > > > Yaswanth Kumar, ying-zheng, Yu > > > > > > > > > > > > > > > > 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, > > > > > > > > Rajini > > > > -- > *Dongjin Lee* > > *A hitchhiker in the mathematical world.* > > *github: <http://goog_969573159/>github.com/dongjinleekr > <http://github.com/dongjinleekr>linkedin: kr.linkedin.com/in/dongjinleekr > <http://kr.linkedin.com/in/dongjinleekr>slideshare: > www.slideshare.net/dongjinleekr > <http://www.slideshare.net/dongjinleekr>* >
