It is my pleasure to announce that the Spring Framework 4.3.1 and 4.2.7 maintenance releases are available now.

The first maintenance release of the 4.3 line contains 40 fixes and improvements and is the base for the upcoming Spring Boot 1.4 release. The master branch has now switched to 5.0 and we'll start merging 5.0 features in preparation for 5.0.0.M1 later this month.

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For more details about Spring Framework 4.3, check Juergen Hoeller's session at SpringOne Platform, which is taking place in Las Vegas between August 1-4 this year. There are many other great talks so check the agenda and get your ticket…

I’m pleased to announce that the spring-kafka (Spring for Apache Kafka) 1.0 GA and Spring Integration Kafka 2.0 GA are available finally!

The artifacts org.springframework.kafka:spring-kafka:1.0.0.RELEASE and org.springframework.kafka:spring-kafka-test:1.0.0.RELEASE are available in the Release repository and Maven Central, respectively.

In addition org.springframework.integration:spring-integration-kafka:2.0.0.RELEASE, fully based on the spring-kafka-1.0.0.RELEASE, is available at the same repositories as well.

Important

Just after release we figured out a nasty bug with unacked offset commits for RECORD mode. Special thanks to Adam Dec! So, please, meet spring-kafka:1.0.1.RELEASE…

On behalf of the team, I am pleased to announce that Service Release 2 of the Spring Cloud Brixton Release Train is available today. The release can be found in our Spring Release repository and Maven Central.

This is primarily a bug fix release.

The following modules were updated as part of Brixton.SR2:

• Spring Cloud Config 1.1.2.RELEASE
• Spring Cloud Consul 1.0.2.RELEASE
• Spring Cloud Netflix 1.1.3.RELEASE
• Spring Cloud Sleuth 1.0.2.RELEASE
• Spring Cloud Zookeeper 1.0.2.RELEASE

And, as always, we welcome feedback: either on GitHub, on gitter, on Stack Overflow, or on Twitter.

The Spring Cloud team will be talking about Spring Cloud at Spring One Platform, which will be taking place in Las Vegas between August 1-4 this year. There are many other great talks so check the agenda and get your ticket…

I am pleased to announce that Gradle dependency management plugin 0.6.0.RELEASE is now available from Maven Central, JCenter, and the Gradle Plugin Portal.

Gradle 3.0 compatibility

This new release is compatible with Gradle 3.0. At the time of writing it's tested against 3.0 M2 and the 0.6.x line will continue to track Gradle 3.0 development to maintain compatibility if at all possible.

Finer control over bom property overrides

Previously, an imported bom's properties could be overridden using project properties. This new release adds support for overriding a property as part of the import. bomProperty can be used to override properties one at a time (and can be used multiple times to override multiple…

I'm pleased to announce the release of Spring Session 1.2.1.RELEASE. This release contains numerous bug fixes and trivial enhancements.

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We are pleased to announce the Spring for Apache Hadoop 2.4.0 GA release.

In addition to version upgrades for Hadoop distros Spring for Apache Hadoop 2.4 adds the following improvements:

• Add build support for HDP 2.4 [SHDP-557]
• Create utils sub-project [SHDP-556]
• Fix issue where NetworkUtils may find wrong default address [SHDP-546]
• Missing trailing slash on spring.yarn.applicationDir path fails to localize [SHDP-562]

See the release changelog for details.

We continue to provide version specific artifacts with their respective transitive dependencies in the Spring IO milestone repository:

• 2.4.0.RELEASE (default - Apache Hadoop stable 2.7.1)
• 2.4.0.RELEASE-phd30 (Pivotal HD 3.0)
• 2.4.0.RELEASE-cdh5 (Cloudera CDH 5.7)
• 2.4.0.RELEASE-hdp23 (Hortonworks HDP 2.3)
• 2.4.0.RELEASE-hdp24 (Hortonworks HDP 2.4)
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On behalf of the team I am pleased to announce the release of Spring Cloud Data Flow 1.0 RC1.

Several exciting new features have been added in this release which carry over to the other Data Flow Server implementations that were also released today.

Data Flow Local Server

Data Flow for Cloud Foundry

Data Flow for Apache YARN

Data Flow for Kubernetes

Data Flow for Apache Mesos

Follow the links above for details on features unique to each individual runtime platform. The highlights of the release are:

• Spring Flo is now an open source project and has been integrated into the Spring Cloud Data Flow dashboard allowing you to visually design data pipelines in your browser.
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I am pleased to announce the 1.0.0.M3 release of Spring Cloud Data Flow for Cloud Foundry, a team effort that encompasses many new features under the hood:

This third milestone builds upon the recent RC1 release of Spring Cloud Data Flow and also adds Cloud Foundry specific refinements. Some highlights include:

• Alignment with Cloud Foundry’s global environment properties such as ORG, API, and URL as opposed to previous naming variants

• Adds security integration to authenticate against OAUTH backend server that’s compatible with Cloud Foundry

• Publishes security configurations for easier overrides when connecting to OAUTH backend server that’s compatible with Cloud Foundry

• Preliminary iterations on performance testing on Cloud Foundry with and without taps’s in real-time streaming pipeline

• Builds upon feature-toggle support from Spring Cloud Data Flow’s core project to conditionally refine what features get included in each release

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On behalf of the Spring Cloud Data Flow team, I am pleased to announce the 1.0.0.RC1 release of Spring Cloud Data Flow for Apache YARN.

Spring Cloud Data Flow for Apache YARN allows one to use all the goodness of Spring Cloud Data Flow (like the Shell and UI) while targeting Apache YARN as a backend. Stream components are deployed as individual apps in Apache YARN, leveraging the power of the platform to handle scaling and health monitoring.

This first release candicate

• Adds several improvements to launching of short-lived applications a.k.a tasks to Apache YARN
• Builds upon Spring StateMachine 1.1.0.RELEASE that includes new features, stability, and API improvements
• Adds support to configure command line args as a separate set of properties to be passed to an application when it's deployed. This is an important requirement for running Spring Batch jobs
• Several Ambari plugin improvements to simplify provisioning of Spring Cloud Data Flow’s YARN server
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