Congrats! Eno
On Thu, Nov 2, 2017 at 10:55 AM, Xin Wang <data.xinw...@gmail.com> wrote: > Great Job! > > - Xin > > 2017-11-02 18:30 GMT+08:00 Paolo Patierno <ppatie...@live.com>: > > > Congratulations for this milestone ! > > > > > > Thanks to Gouzhang for running the release ! > > > > > > Paolo Patierno > > Senior Software Engineer (IoT) @ Red Hat > > Microsoft MVP on Azure & IoT > > Microsoft Azure Advisor > > > > Twitter : @ppatierno<http://twitter.com/ppatierno> > > Linkedin : paolopatierno<http://it.linkedin.com/in/paolopatierno> > > Blog : DevExperience<http://paolopatierno.wordpress.com/> > > > > > > ________________________________ > > From: Jaikiran Pai <jai.forums2...@gmail.com> > > Sent: Thursday, November 2, 2017 2:59 AM > > To: dev@kafka.apache.org > > Cc: Users > > Subject: Re: [ANNOUNCE] Apache Kafka 1.0.0 Released > > > > Congratulations Kafka team on the release. Happy to see Kafka reach this > > milestone. It has been a pleasure using Kafka and also interacting with > > the Kafka team. > > > > -Jaikiran > > > > > > On 01/11/17 7:57 PM, Guozhang Wang wrote: > > > The Apache Kafka community is pleased to announce the release for > Apache > > > Kafka 1.0.0. > > > > > > This is a major release of the Kafka project, and is no mere bump of > the > > > version number. The Apache Kafka Project Management Committee has > packed > > a > > > number of valuable enhancements into the release. Let me summarize a > few > > of > > > them: > > > > > > ** Since its introduction in version 0.10, the Streams API has become > > > hugely popular among Kafka users, including the likes of Pinterest, > > > Rabobank, Zalando, and The New York Times. In 1.0, the the API > continues > > to > > > evolve at a healthy pace. To begin with, the builder API has been > > improved > > > (KIP-120). A new API has been added to expose the state of active tasks > > at > > > runtime (KIP-130). Debuggability gets easier with enhancements to the > > > print() and writeAsText() methods (KIP-160). And if that’s not enough, > > > check out KIP-138 and KIP-161 too. For more on streams, check out the > > > Apache Kafka Streams documentation (https://kafka.apache.org/docu > > > mentation/streams/), including some helpful new tutorial videos. > > > > > > ** Operating Kafka at scale requires that the system remain observable, > > and > > > to make that easier, we’ve made a number of improvements to metrics. > > These > > > are too many to summarize without becoming tedious, but Connect metrics > > > have been significantly improved (KIP-196), a litany of new health > check > > > metrics are now exposed (KIP-188), and we now have a global topic and > > > partition count (KIP-168). Check out KIP-164 and KIP-187 for even more. > > > > > > ** We now support Java 9, leading, among other things, to significantly > > > faster TLS and CRC32C implementations. Over-the-wire encryption will be > > > faster now, which will keep Kafka fast and compute costs low when > > > encryption is enabled. > > > > > > ** In keeping with the security theme, KIP-152 cleans up the error > > handling > > > on Simple Authentication Security Layer (SASL) authentication attempts. > > > Previously, some authentication error conditions were indistinguishable > > > from broker failures and were not logged in a clear way. This is > cleaner > > > now. > > > > > > ** Kafka can now tolerate disk failures better. Historically, JBOD > > storage > > > configurations have not been recommended, but the architecture has > > > nevertheless been tempting: after all, why not rely on Kafka’s own > > > replication mechanism to protect against storage failure rather than > > using > > > RAID? With KIP-112, Kafka now handles disk failure more gracefully. A > > > single disk failure in a JBOD broker will not bring the entire broker > > down; > > > rather, the broker will continue serving any log files that remain on > > > functioning disks. > > > > > > ** Since release 0.11.0, the idempotent producer (which is the producer > > > used in the presence of a transaction, which of course is the producer > we > > > use for exactly-once processing) required max.in.flight.requests.per. > > connection > > > to be equal to one. As anyone who has written or tested a wire protocol > > can > > > attest, this put an upper bound on throughput. Thanks to KAFKA-5949, > this > > > can now be as large as five, relaxing the throughput constraint quite a > > bit. > > > > > > > > > All of the changes in this release can be found in the release notes: > > > > > > https://dist.apache.org/repos/dist/release/kafka/1.0.0/ > > RELEASE_NOTES.html > > > > > > > > > You can download the source release from: > > > > > > https://www.apache.org/dyn/closer.cgi?path=/kafka/1.0.0/ > > kafka-1.0.0-src.tgz > > > > > > and binary releases from: > > > > > > https://www.apache.org/dyn/closer.cgi?path=/kafka/1.0.0/ > > kafka_2.11-1.0.0.tgz > > > (Scala > > > 2.11) > > > https://www.apache.org/dyn/closer.cgi?path=/kafka/1.0.0/ > > kafka_2.12-1.0.0.tgz > > > (Scala > > > 2.12) > > > > > > > > > ------------------------------------------------------------ > > > --------------------------------------- > > > > > > Apache Kafka is a distributed streaming platform with four 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.three key capabilities: > > > > > > > > > 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 108 contributors to this release! > > > > > > Abhishek Mendhekar, Xi Hu, Andras Beni, Andrey Dyachkov, Andy Chambers, > > > Apurva Mehta, Armin Braun, Attila Kreiner, Balint Molnar, Bart De > Vylder, > > > Ben Stopford, Bharat Viswanadham, Bill Bejeck, Boyang Chen, Bryan > > Baugher, > > > Colin P. Mccabe, Koen De Groote, Dale Peakall, Damian Guy, Dana Powers, > > > Dejan Stojadinović, Derrick Or, Dong Lin, Zhendong Liu, Dustin Cote, > > > Edoardo Comar, Eno Thereska, Erik Kringen, Erkan Unal, Evgeny > > Veretennikov, > > > Ewen Cheslack-Postava, Florian Hussonnois, Janek P, Gregor Uhlenheuer, > > > Guozhang Wang, Gwen Shapira, Hamidreza Afzali, Hao Chen, Jiefang He, > > Holden > > > Karau, Hooman Broujerdi, Hugo Louro, Ismael Juma, Jacek Laskowski, > Jakub > > > Scholz, James Cheng, James Chien, Jan Burkhardt, Jason Gustafson, Jeff > > > Chao, Jeff Klukas, Jeff Widman, Jeremy Custenborder, Jeyhun Karimov, > > > Jiangjie Qin, Joel Dice, Joel Hamill, Jorge Quilcate Otoya, Kamal C, > > Kelvin > > > Rutt, Kevin Lu, Kevin Sweeney, Konstantine Karantasis, Perry Lee, > Magnus > > > Edenhill, Manikumar Reddy, Manikumar Reddy O, Manjula Kumar, Mariam > John, > > > Mario Molina, Matthias J. Sax, Max Zheng, Michael Andre Pearce, Michael > > > André Pearce, Michael G. Noll, Michal Borowiecki, Mickael Maison, Nick > > > Pillitteri, Oleg Prozorov, Onur Karaman, Paolo Patierno, Pranav Maniar, > > > Qihuang Zheng, Radai Rosenblatt, Alex Radzish, Rajini Sivaram, Randall > > > Hauch, Richard Yu, Robin Moffatt, Sean McCauliff, Sebastian Gavril, > Siva > > > Santhalingam, Soenke Liebau, Stephane Maarek, Stephane Roset, Ted Yu, > > > Thibaud Chardonnens, Tom Bentley, Tommy Becker, Umesh Chaudhary, Vahid > > > Hashemian, Vladimír Kleštinec, Xavier Léauté, Xianyang Liu, Xin Li, > > Linhua > > > Xin > > > > > > > > > We welcome your help and feedback. For more information on how to > report > > > problems, and to get involved, visit the project website at > > > http://kafka.apache.org/ > > > > > > > > > > > > > > > Thanks, > > > Guozhang Wang > > > > > > > > > > -- > Thanks, > Xin >
