Great milestone ! Thanks for running this release.
On Thu, Nov 2, 2017 at 11:10 AM, Eno Thereska <eno.there...@gmail.com> wrote: > 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 >>
