This document describes how to release Apache Kafka from trunk.
It is a work in progress and should be refined by the Release Manager (RM) as they come across aspects of the release process not yet documented here.
NOTE: For the purpose of illustration, this document assumes that the version being released is 0.10.0.0 and the following development version will become 0.10.1.0.
Prepare release plan in the wiki, notifying the community the overall plan and goals for the release (For example: Release Plan 0.10.0)
Go over JIRA for the release and make sure that blockers are marked as blockers and non-blockers are non-blockers. This JIRA filter may be handy:
project = KAFKA AND fixVersion = 0.10.0.0 AND resolution = Unresolved AND priority = blocker ORDER BY due ASC, priority DESC, created ASC |
It is important that between the time that the release plan is voted to the time when the release branch is created, no experimental or potentially destabilizing work is checked into the trunk. While it is acceptable to introduce major changes, they must be thoroughly reviewed and have good test coverage to ensure that the release branch does not start of being unstable. If necessary the RM can discuss if certain issues should be fixed on the trunk in this time, and if so what is the gating criteria for accepting them.
Skip this section if you are releasing a bug fix version (e.g. 2.2.1).
Send email announcing the new branch:
To: dev@kafka.apache.org Subject: New release branch 0.10.0 Hello Kafka developers and friends, As promised, we now have a release branch for 0.10.0 release (with 0.10.0.0 as the version). Trunk has been bumped to 0.10.1.0-SNAPSHOT. I'll be going over the JIRAs to move every non-blocker from this release to the next release. From this point, most changes should go to trunk. *Blockers (existing and new that we discover while testing the release) will be double-committed. *Please discuss with your reviewer whether your PR should go to trunk or to trunk+release so they can merge accordingly. *Please help us test the release! * Thanks! $RM |
We should improve the release script to include these steps. In the meantime, for new releases:
Send a vote closing email:
To: dev@kafka.apache.org Subject: [RESULTS] [VOTE] Release Kafka version 0.10.0.0 This vote passes with 7 +1 votes (3 bindings) and no 0 or -1 votes. +1 votes PMC Members: * $Name * $Name * $Name Committers: * $Name * $Name Community: * $Name * $Name 0 votes * No votes -1 votes * No votes Vote thread: http://markmail.org/message/faioizetvcils2zo I'll continue with the release process and the release announcement will follow in the next few days. $RM |
Make sure the KEYS file in the svn repo includes the committer who signed the release.
The KEYS must be in https://www.apache.org/dist/kafka/KEYS and not just in http://kafka.apache.org/KEYS.
svn commit -m "Release 0.10.0.0"
note: you need to be subscribed to `kafka-clients@googlegroups.com` with you apache email address – otherwise it bounces back
Use the previously generated email template using `release.py` script (or) Use the below email template (maybe update Scala versions accordingly):
The Apache Kafka community is pleased to announce the release for Apache Kafka <release-number>. This is a bug fix release and it includes fixes and improvements from <#> JIRAs, including a few critical bugs. All of the changes in this release can be found in the release notes: https://www.apache.org/dist/kafka/<release-number>/RELEASE_NOTES.html You can download the source and binary release (Scala 2.11 and Scala 2.12) from: https://kafka.apache.org/downloads#<release-number> --------------------------------------------------------------------------------------------------- Apache Kafka is a distributed streaming platform with four core APIs: ** The Producer API allows an application to publish a stream records to one or more Kafka topics. ** The Consumer API allows an application to subscribe to one or more topics and process the stream of records produced to them. ** The Streams API allows an application to act as a stream processor, consuming an input stream from one or more topics and producing an output stream to one or more output topics, effectively transforming the input streams to output streams. ** The Connector API allows building and running reusable producers or consumers that connect Kafka topics to existing applications or data systems. For example, a connector to a relational database might capture every change to a table. With these APIs, Kafka can be used for two broad classes of application: ** Building real-time streaming data pipelines that reliably get data between systems or applications. ** Building real-time streaming applications that transform or react to the streams of data. Apache Kafka is in use at large and small companies worldwide, including Capital One, Goldman Sachs, ING, LinkedIn, Netflix, Pinterest, Rabobank, Target, The New York Times, Uber, Yelp, and Zalando, among others. A big thank you for the following <#> contributors to this release! <list-of-contributors> We welcome your help and feedback. For more information on how to report problems, and to get involved, visit the project website at https://kafka.apache.org/ Thank you! Regards, $RM |