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Posted to dev@kafka.apache.org by Guozhang Wang <wa...@gmail.com> on 2017/11/01 14:27:11 UTC
[ANNOUNCE] Apache Kafka 1.0.0 Released
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
Re: [ANNOUNCE] Apache Kafka 1.0.0 Released
Posted by James Cheng <wu...@gmail.com>.
Good job, everyone!
And thanks Guozhang for running the release!
-James
> On Nov 1, 2017, at 7:27 AM, Guozhang Wang <wa...@gmail.com> 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
Re: [ANNOUNCE] Apache Kafka 1.0.0 Released
Posted by Rajini Sivaram <ra...@gmail.com>.
Guozhang,
Thank you for running the release!
Regards,
Rajini
On Thu, Nov 2, 2017 at 12:07 PM, UMESH CHAUDHARY <um...@gmail.com>
wrote:
> Great news, Congratulations to the team !
>
> On Thu, 2 Nov 2017 at 17:17 Damian Guy <da...@gmail.com> wrote:
>
> > Thanks Guozhang!
> >
> > On Thu, 2 Nov 2017 at 11:42 Ismael Juma <is...@gmail.com> wrote:
> >
> > > Thanks for running the release, Guozhang! Also thanks to all the
> > > contributors who made 1.0 possible. :)
> > >
> > > Ismael
> > >
> > > On 1 Nov 2017 2:27 pm, "Guozhang Wang" <wa...@gmail.com> 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/ <https://kafka.apache.org/documentation/streams/> <
> > > https://kafka.apache.org/documentation/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.con
> > > nection
> > > 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
> > >
> >
>
Re: [ANNOUNCE] Apache Kafka 1.0.0 Released
Posted by Becket Qin <be...@gmail.com>.
Great news! Thanks for running the release, Guozhang!
On Thu, Nov 2, 2017 at 8:19 AM, Vahid S Hashemian <vahidhashemian@us.ibm.com
> wrote:
> Great news. Thanks Guozhang!
>
> --Vahid
>
>
>
>
> From: Rajini Sivaram <ra...@gmail.com>
> To: dev <de...@kafka.apache.org>
> Date: 11/02/2017 05:37 AM
> Subject: Re: [ANNOUNCE] Apache Kafka 1.0.0 Released
>
>
>
> Guozhang,
>
> Thank you for running the release!
>
> Regards,
>
> Rajini
>
> On Thu, Nov 2, 2017 at 12:07 PM, UMESH CHAUDHARY <um...@gmail.com>
> wrote:
>
> > Great news, Congratulations to the team !
> >
> > On Thu, 2 Nov 2017 at 17:17 Damian Guy <da...@gmail.com> wrote:
> >
> > > Thanks Guozhang!
> > >
> > > On Thu, 2 Nov 2017 at 11:42 Ismael Juma <is...@gmail.com> wrote:
> > >
> > > > Thanks for running the release, Guozhang! Also thanks to all the
> > > > contributors who made 1.0 possible. :)
> > > >
> > > > Ismael
> > > >
> > > > On 1 Nov 2017 2:27 pm, "Guozhang Wang" <wa...@gmail.com> 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://urldefense.proofpoint.com/v2/url?u=https-3A__kafka.
> apache.org_docu&d=DwIFaQ&c=jf_iaSHvJObTbx-siA1ZOg&r=Q_
> itwloTQj3_xUKl7Nzswo6KE4Nj-kjJc7uSVcviKUc&m=tq2Tesrs2V9c_
> JVNIBL_Hk-AvVv8hGn62gT7pdR-6-g&s=Be3Toa7cHgFiUMCDAnwJ_
> e7YhTUvp4eY84rXbSA4Irc&e=
>
> > > > mentation/streams/ <
> https://urldefense.proofpoint.com/v2/url?u=https-3A__kafka.
> apache.org_documentation_streams_&d=DwIFaQ&c=jf_iaSHvJObTbx-siA1ZOg&r=Q_
> itwloTQj3_xUKl7Nzswo6KE4Nj-kjJc7uSVcviKUc&m=tq2Tesrs2V9c_
> JVNIBL_Hk-AvVv8hGn62gT7pdR-6-g&s=_75tvKAxc9SOMmWlh2Kwo9lsbZjl0Xd
> AQUpfH8pP_bs&e=
> > <
> > > >
> https://urldefense.proofpoint.com/v2/url?u=https-3A__kafka.
> apache.org_documentation_streams_&d=DwIFaQ&c=jf_iaSHvJObTbx-siA1ZOg&r=Q_
> itwloTQj3_xUKl7Nzswo6KE4Nj-kjJc7uSVcviKUc&m=tq2Tesrs2V9c_
> JVNIBL_Hk-AvVv8hGn62gT7pdR-6-g&s=_75tvKAxc9SOMmWlh2Kwo9lsbZjl0Xd
> AQUpfH8pP_bs&e=
> >),
> > > > 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.con
> > > > nection
> > > > 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://urldefense.proofpoint.com/v2/url?u=https-3A__dist.
> apache.org_repos_dist_release_kafka_1.0.0_&d=DwIFaQ&c=jf_
> iaSHvJObTbx-siA1ZOg&r=Q_itwloTQj3_xUKl7Nzswo6KE4Nj-
> kjJc7uSVcviKUc&m=tq2Tesrs2V9c_JVNIBL_Hk-AvVv8hGn62gT7pdR-6-
> g&s=AXo0pEvav_6TS4Wqpd_k46wKszuEo8nr29riGnDhTTQ&e=
>
> > RELEASE_NOTES.html
> > > >
> > > >
> > > > You can download the source release from:
> > > >
> > > >
> > >
> https://urldefense.proofpoint.com/v2/url?u=https-3A__www.
> apache.org_dyn_closer.cgi-3Fpath-3D_kafka_1.0.0_&d=
> DwIFaQ&c=jf_iaSHvJObTbx-siA1ZOg&r=Q_itwloTQj3_xUKl7Nzswo6KE4Nj-
> kjJc7uSVcviKUc&m=tq2Tesrs2V9c_JVNIBL_Hk-AvVv8hGn62gT7pdR-6-g&s=-
> ui4P2xjndxAXFEw5L2Ri8JXjtw1z5H9jJL2GQVv-UM&e=
>
> > kafka-1.0.0-src.tgz
> > > >
> > > > and binary releases from:
> > > >
> > > >
> > > >
> > >
> https://urldefense.proofpoint.com/v2/url?u=https-3A__www.
> apache.org_dyn_closer.cgi-3Fpath-3D_kafka_1.0.0_&d=
> DwIFaQ&c=jf_iaSHvJObTbx-siA1ZOg&r=Q_itwloTQj3_xUKl7Nzswo6KE4Nj-
> kjJc7uSVcviKUc&m=tq2Tesrs2V9c_JVNIBL_Hk-AvVv8hGn62gT7pdR-6-g&s=-
> ui4P2xjndxAXFEw5L2Ri8JXjtw1z5H9jJL2GQVv-UM&e=
>
> > kafka_2.11-1.0.0.tgz
> > > > (Scala
> > > > 2.11)
> > > >
> > > >
> > >
> https://urldefense.proofpoint.com/v2/url?u=https-3A__www.
> apache.org_dyn_closer.cgi-3Fpath-3D_kafka_1.0.0_&d=
> DwIFaQ&c=jf_iaSHvJObTbx-siA1ZOg&r=Q_itwloTQj3_xUKl7Nzswo6KE4Nj-
> kjJc7uSVcviKUc&m=tq2Tesrs2V9c_JVNIBL_Hk-AvVv8hGn62gT7pdR-6-g&s=-
> ui4P2xjndxAXFEw5L2Ri8JXjtw1z5H9jJL2GQVv-UM&e=
>
> > 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
> > > >
> https://urldefense.proofpoint.com/v2/url?u=http-3A__kafka.
> apache.org_&d=DwIFaQ&c=jf_iaSHvJObTbx-siA1ZOg&r=Q_
> itwloTQj3_xUKl7Nzswo6KE4Nj-kjJc7uSVcviKUc&m=tq2Tesrs2V9c_
> JVNIBL_Hk-AvVv8hGn62gT7pdR-6-g&s=aV-3Zgf98aWeXp-
> jZ3XE1BwYflwjvyMRB37izHzmTIw&e=
>
> > > >
> > > >
> > > >
> > > >
> > > > Thanks,
> > > > Guozhang Wang
> > > >
> > >
> >
>
>
>
>
>
Re: [ANNOUNCE] Apache Kafka 1.0.0 Released
Posted by Vahid S Hashemian <va...@us.ibm.com>.
Great news. Thanks Guozhang!
--Vahid
From: Rajini Sivaram <ra...@gmail.com>
To: dev <de...@kafka.apache.org>
Date: 11/02/2017 05:37 AM
Subject: Re: [ANNOUNCE] Apache Kafka 1.0.0 Released
Guozhang,
Thank you for running the release!
Regards,
Rajini
On Thu, Nov 2, 2017 at 12:07 PM, UMESH CHAUDHARY <um...@gmail.com>
wrote:
> Great news, Congratulations to the team !
>
> On Thu, 2 Nov 2017 at 17:17 Damian Guy <da...@gmail.com> wrote:
>
> > Thanks Guozhang!
> >
> > On Thu, 2 Nov 2017 at 11:42 Ismael Juma <is...@gmail.com> wrote:
> >
> > > Thanks for running the release, Guozhang! Also thanks to all the
> > > contributors who made 1.0 possible. :)
> > >
> > > Ismael
> > >
> > > On 1 Nov 2017 2:27 pm, "Guozhang Wang" <wa...@gmail.com> 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://urldefense.proofpoint.com/v2/url?u=https-3A__kafka.apache.org_docu&d=DwIFaQ&c=jf_iaSHvJObTbx-siA1ZOg&r=Q_itwloTQj3_xUKl7Nzswo6KE4Nj-kjJc7uSVcviKUc&m=tq2Tesrs2V9c_JVNIBL_Hk-AvVv8hGn62gT7pdR-6-g&s=Be3Toa7cHgFiUMCDAnwJ_e7YhTUvp4eY84rXbSA4Irc&e=
> > > mentation/streams/ <
https://urldefense.proofpoint.com/v2/url?u=https-3A__kafka.apache.org_documentation_streams_&d=DwIFaQ&c=jf_iaSHvJObTbx-siA1ZOg&r=Q_itwloTQj3_xUKl7Nzswo6KE4Nj-kjJc7uSVcviKUc&m=tq2Tesrs2V9c_JVNIBL_Hk-AvVv8hGn62gT7pdR-6-g&s=_75tvKAxc9SOMmWlh2Kwo9lsbZjl0XdAQUpfH8pP_bs&e=
> <
> > >
https://urldefense.proofpoint.com/v2/url?u=https-3A__kafka.apache.org_documentation_streams_&d=DwIFaQ&c=jf_iaSHvJObTbx-siA1ZOg&r=Q_itwloTQj3_xUKl7Nzswo6KE4Nj-kjJc7uSVcviKUc&m=tq2Tesrs2V9c_JVNIBL_Hk-AvVv8hGn62gT7pdR-6-g&s=_75tvKAxc9SOMmWlh2Kwo9lsbZjl0XdAQUpfH8pP_bs&e=
>),
> > > 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.con
> > > nection
> > > 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://urldefense.proofpoint.com/v2/url?u=https-3A__dist.apache.org_repos_dist_release_kafka_1.0.0_&d=DwIFaQ&c=jf_iaSHvJObTbx-siA1ZOg&r=Q_itwloTQj3_xUKl7Nzswo6KE4Nj-kjJc7uSVcviKUc&m=tq2Tesrs2V9c_JVNIBL_Hk-AvVv8hGn62gT7pdR-6-g&s=AXo0pEvav_6TS4Wqpd_k46wKszuEo8nr29riGnDhTTQ&e=
> RELEASE_NOTES.html
> > >
> > >
> > > You can download the source release from:
> > >
> > >
> >
https://urldefense.proofpoint.com/v2/url?u=https-3A__www.apache.org_dyn_closer.cgi-3Fpath-3D_kafka_1.0.0_&d=DwIFaQ&c=jf_iaSHvJObTbx-siA1ZOg&r=Q_itwloTQj3_xUKl7Nzswo6KE4Nj-kjJc7uSVcviKUc&m=tq2Tesrs2V9c_JVNIBL_Hk-AvVv8hGn62gT7pdR-6-g&s=-ui4P2xjndxAXFEw5L2Ri8JXjtw1z5H9jJL2GQVv-UM&e=
> kafka-1.0.0-src.tgz
> > >
> > > and binary releases from:
> > >
> > >
> > >
> >
https://urldefense.proofpoint.com/v2/url?u=https-3A__www.apache.org_dyn_closer.cgi-3Fpath-3D_kafka_1.0.0_&d=DwIFaQ&c=jf_iaSHvJObTbx-siA1ZOg&r=Q_itwloTQj3_xUKl7Nzswo6KE4Nj-kjJc7uSVcviKUc&m=tq2Tesrs2V9c_JVNIBL_Hk-AvVv8hGn62gT7pdR-6-g&s=-ui4P2xjndxAXFEw5L2Ri8JXjtw1z5H9jJL2GQVv-UM&e=
> kafka_2.11-1.0.0.tgz
> > > (Scala
> > > 2.11)
> > >
> > >
> >
https://urldefense.proofpoint.com/v2/url?u=https-3A__www.apache.org_dyn_closer.cgi-3Fpath-3D_kafka_1.0.0_&d=DwIFaQ&c=jf_iaSHvJObTbx-siA1ZOg&r=Q_itwloTQj3_xUKl7Nzswo6KE4Nj-kjJc7uSVcviKUc&m=tq2Tesrs2V9c_JVNIBL_Hk-AvVv8hGn62gT7pdR-6-g&s=-ui4P2xjndxAXFEw5L2Ri8JXjtw1z5H9jJL2GQVv-UM&e=
> 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
> > >
https://urldefense.proofpoint.com/v2/url?u=http-3A__kafka.apache.org_&d=DwIFaQ&c=jf_iaSHvJObTbx-siA1ZOg&r=Q_itwloTQj3_xUKl7Nzswo6KE4Nj-kjJc7uSVcviKUc&m=tq2Tesrs2V9c_JVNIBL_Hk-AvVv8hGn62gT7pdR-6-g&s=aV-3Zgf98aWeXp-jZ3XE1BwYflwjvyMRB37izHzmTIw&e=
> > >
> > >
> > >
> > >
> > > Thanks,
> > > Guozhang Wang
> > >
> >
>
Re: [ANNOUNCE] Apache Kafka 1.0.0 Released
Posted by UMESH CHAUDHARY <um...@gmail.com>.
Great news, Congratulations to the team !
On Thu, 2 Nov 2017 at 17:17 Damian Guy <da...@gmail.com> wrote:
> Thanks Guozhang!
>
> On Thu, 2 Nov 2017 at 11:42 Ismael Juma <is...@gmail.com> wrote:
>
> > Thanks for running the release, Guozhang! Also thanks to all the
> > contributors who made 1.0 possible. :)
> >
> > Ismael
> >
> > On 1 Nov 2017 2:27 pm, "Guozhang Wang" <wa...@gmail.com> 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/ <https://kafka.apache.org/documentation/streams/> <
> > https://kafka.apache.org/documentation/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.con
> > nection
> > 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
> >
>
Re: [ANNOUNCE] Apache Kafka 1.0.0 Released
Posted by UMESH CHAUDHARY <um...@gmail.com>.
Great news, Congratulations to the team !
On Thu, 2 Nov 2017 at 17:17 Damian Guy <da...@gmail.com> wrote:
> Thanks Guozhang!
>
> On Thu, 2 Nov 2017 at 11:42 Ismael Juma <is...@gmail.com> wrote:
>
> > Thanks for running the release, Guozhang! Also thanks to all the
> > contributors who made 1.0 possible. :)
> >
> > Ismael
> >
> > On 1 Nov 2017 2:27 pm, "Guozhang Wang" <wa...@gmail.com> 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/ <https://kafka.apache.org/documentation/streams/> <
> > https://kafka.apache.org/documentation/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.con
> > nection
> > 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
> >
>
Re: [ANNOUNCE] Apache Kafka 1.0.0 Released
Posted by Damian Guy <da...@gmail.com>.
Thanks Guozhang!
On Thu, 2 Nov 2017 at 11:42 Ismael Juma <is...@gmail.com> wrote:
> Thanks for running the release, Guozhang! Also thanks to all the
> contributors who made 1.0 possible. :)
>
> Ismael
>
> On 1 Nov 2017 2:27 pm, "Guozhang Wang" <wa...@gmail.com> 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/ <https://kafka.apache.org/documentation/streams/> <
> https://kafka.apache.org/documentation/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.con
> nection
> 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
>
Re: [ANNOUNCE] Apache Kafka 1.0.0 Released
Posted by Damian Guy <da...@gmail.com>.
Thanks Guozhang!
On Thu, 2 Nov 2017 at 11:42 Ismael Juma <is...@gmail.com> wrote:
> Thanks for running the release, Guozhang! Also thanks to all the
> contributors who made 1.0 possible. :)
>
> Ismael
>
> On 1 Nov 2017 2:27 pm, "Guozhang Wang" <wa...@gmail.com> 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/ <https://kafka.apache.org/documentation/streams/> <
> https://kafka.apache.org/documentation/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.con
> nection
> 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
>
Re: [ANNOUNCE] Apache Kafka 1.0.0 Released
Posted by Ismael Juma <is...@gmail.com>.
Thanks for running the release, Guozhang! Also thanks to all the
contributors who made 1.0 possible. :)
Ismael
On 1 Nov 2017 2:27 pm, "Guozhang Wang" <wa...@gmail.com> 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/ <https://kafka.apache.org/documentation/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.con
nection
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
Re: [ANNOUNCE] Apache Kafka 1.0.0 Released
Posted by Ismael Juma <is...@gmail.com>.
Thanks for running the release, Guozhang! Also thanks to all the
contributors who made 1.0 possible. :)
Ismael
On 1 Nov 2017 2:27 pm, "Guozhang Wang" <wa...@gmail.com> 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/ <https://kafka.apache.org/documentation/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.con
nection
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
Re: [ANNOUNCE] Apache Kafka 1.0.0 Released
Posted by Tom Bentley <t....@gmail.com>.
Thanks Guozhang!
On 2 November 2017 at 11:22, Mickael Maison <mi...@gmail.com>
wrote:
> Great milestone ! Thanks for running this release.
>
> On Thu, Nov 2, 2017 at 11:10 AM, Eno Thereska <en...@gmail.com>
> wrote:
> > Congrats!
> >
> > Eno
> >
> > On Thu, Nov 2, 2017 at 10:55 AM, Xin Wang <da...@gmail.com>
> wrote:
> >
> >> Great Job!
> >>
> >> - Xin
> >>
> >> 2017-11-02 18:30 GMT+08:00 Paolo Patierno <pp...@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 <ja...@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
> >>
>
Re: [ANNOUNCE] Apache Kafka 1.0.0 Released
Posted by Mickael Maison <mi...@gmail.com>.
Great milestone ! Thanks for running this release.
On Thu, Nov 2, 2017 at 11:10 AM, Eno Thereska <en...@gmail.com> wrote:
> Congrats!
>
> Eno
>
> On Thu, Nov 2, 2017 at 10:55 AM, Xin Wang <da...@gmail.com> wrote:
>
>> Great Job!
>>
>> - Xin
>>
>> 2017-11-02 18:30 GMT+08:00 Paolo Patierno <pp...@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 <ja...@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
>>
Re: [ANNOUNCE] Apache Kafka 1.0.0 Released
Posted by Eno Thereska <en...@gmail.com>.
Congrats!
Eno
On Thu, Nov 2, 2017 at 10:55 AM, Xin Wang <da...@gmail.com> wrote:
> Great Job!
>
> - Xin
>
> 2017-11-02 18:30 GMT+08:00 Paolo Patierno <pp...@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 <ja...@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
>
Re: [ANNOUNCE] Apache Kafka 1.0.0 Released
Posted by Xin Wang <da...@gmail.com>.
Great Job!
- Xin
2017-11-02 18:30 GMT+08:00 Paolo Patierno <pp...@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 <ja...@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
Re: [ANNOUNCE] Apache Kafka 1.0.0 Released
Posted by Xin Wang <da...@gmail.com>.
Great Job!
- Xin
2017-11-02 18:30 GMT+08:00 Paolo Patierno <pp...@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 <ja...@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
Re: [ANNOUNCE] Apache Kafka 1.0.0 Released
Posted by Paolo Patierno <pp...@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 <ja...@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
>
Re: [ANNOUNCE] Apache Kafka 1.0.0 Released
Posted by Paolo Patierno <pp...@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 <ja...@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
>
Re: [ANNOUNCE] Apache Kafka 1.0.0 Released
Posted by Jaikiran Pai <ja...@gmail.com>.
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
>
Re: [kafka-clients] [ANNOUNCE] Apache Kafka 1.0.0 Released
Posted by Jun Rao <ju...@confluent.io>.
Guozhang,
Thanks for running the release!
Jun
On Wed, Nov 1, 2017 at 7:27 AM, Guozhang Wang <wa...@gmail.com> 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/kafk
> a-1.0.0-src.tgz
>
> and binary releases from:
>
> https://www.apache.org/dyn/closer.cgi?path=/kafka/1.0.0/kafk
> a_2.11-1.0.0.tgz (Scala 2.11)
> https://www.apache.org/dyn/closer.cgi?path=/kafka/1.0.0/kafk
> a_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
>
> --
> You received this message because you are subscribed to the Google Groups
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> To view this discussion on the web visit https://groups.google.com/d/
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> For more options, visit https://groups.google.com/d/optout.
>
Re: [ANNOUNCE] Apache Kafka 1.0.0 Released
Posted by James Cheng <wu...@gmail.com>.
Good job, everyone!
And thanks Guozhang for running the release!
-James
> On Nov 1, 2017, at 7:27 AM, Guozhang Wang <wa...@gmail.com> 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
Re: [kafka-clients] [ANNOUNCE] Apache Kafka 1.0.0 Released
Posted by Jun Rao <ju...@confluent.io>.
Guozhang,
Thanks for running the release!
Jun
On Wed, Nov 1, 2017 at 7:27 AM, Guozhang Wang <wa...@gmail.com> 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/kafk
> a-1.0.0-src.tgz
>
> and binary releases from:
>
> https://www.apache.org/dyn/closer.cgi?path=/kafka/1.0.0/kafk
> a_2.11-1.0.0.tgz (Scala 2.11)
> https://www.apache.org/dyn/closer.cgi?path=/kafka/1.0.0/kafk
> a_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
>
> --
> You received this message because you are subscribed to the Google Groups
> "kafka-clients" group.
> To unsubscribe from this group and stop receiving emails from it, send an
> email to kafka-clients+unsubscribe@googlegroups.com.
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> Visit this group at https://groups.google.com/group/kafka-clients.
> To view this discussion on the web visit https://groups.google.com/d/
> msgid/kafka-clients/CAHwHRrVP8B4_bSNqDoMWVufM07NPLFe%3DoN_
> Mk5QyHZSs8yODOQ%40mail.gmail.com
> <https://groups.google.com/d/msgid/kafka-clients/CAHwHRrVP8B4_bSNqDoMWVufM07NPLFe%3DoN_Mk5QyHZSs8yODOQ%40mail.gmail.com?utm_medium=email&utm_source=footer>
> .
> For more options, visit https://groups.google.com/d/optout.
>
Re: [ANNOUNCE] Apache Kafka 1.0.0 Released
Posted by Jaikiran Pai <ja...@gmail.com>.
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
>