I am pleased to announce that the Spring for Apache Kafka 1.1.0.RELEASE is now available in the spring release repo and Maven Central.

Due to some community requirements, we decided to bypass the Release Candidate (RC) phase and released General Availability (GA) immediately.

There are not many changes since the previous Milestone 2, but here is a summary of all Spring Kafka 1.1 changes:

• Apache Kafka 0.10 upgrade;

• The batch of messages support via BatchMessageListener as well as via @KafkaListener annotation configuration;

• The null payload concept support via KafkaNull placeholder object;

• You can now perform seek operations from the listener - this allows setting an initial offset when partitions are assigned by Kafka when using group management. You can also perform arbitrary seek operations after initialization;

• Allow setting the initial offset to be relative to the current offset;

• The KafkaTemplate now provides access to the metrics and partitionsFor methods on the Producer.

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I’m pleased to announce that Spring Integration maintenance version 4.3.2 has been released. It is available in the spring release repo and Maven Central. It’s strongly recommended for everyone to upgrade because of the bug fixes and improvements contained in the release.

While you can find all the changes for 4.3.2 in its Release Notes, here are some highlights:

• It is a foundation for upcoming Spring Boot 1.4.1;

• The RmiOutboundGateway now can be supplied with RmiProxyFactoryBeanConfigurer to get access to underlying RmiProxyFactoryBean for customization, e.g. ContextPropagatingRemoteInvocationFactory;

• Added TcpConnectionFailedEvent - An event emitted when a connection could not be established for some reason;

• The spring.integration.readOnly.headers global integration property to let to exclude some headers from replying, e.g. undesired or incompatible contentType, populated by some transformers by default.

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On behalf of the team, I am happy to announce that the Spring Framework 4.3.3 and 4.2.8 maintenance releases are available now.

This third maintenance release of the 4.3 line contains over 60 fixes and improvements and is the base for the upcoming Spring Boot 1.4.1 release later this week. We'll also release another Spring Framework 5.0 milestone Wednesday so stay tuned for more release announcements!

Project Page | GitHub | Issues | Documentation

On behalf of the team, I am excited to announce the release of the first milestone of Spring Cloud Data Flow 1.1 along with a 1.0.1 maintenance release for the 1.0 version.

Note: A great way to start using this new release(s) is to follow the release matrix on the project page, which includes the download coordinates and the links to the reference guide.

1.1 M1 release

Over the last few weeks, we have added new features and improvements to the overall orchestration of data microservices. The following new features were included in the 1.1.0.M1 release:

Security

• Adds LDAP backend-authentication
• Adds Basic backend-authentication
• Adds File backend-authentication
• Improvements to OAUTH backed-authentication
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I’m pleased to announce that the Java DSL for Spring Integration 1.2 M2 is available now!

First of all I’d like to thank everyone who created issues, raised Pull Requests, provided feedback or just asked questions on StackOverflow. Especial thanks for early adopters since the previous Milestone 1. With their help we have improved and fixed some issues with runtime flow registration.

The artifact org.springframework.integration:spring-integration-java-dsl:1.2.0.M2 is available in the Milestone repo. So, give it a shot and don’t hesitate to raise a GH issue for any feedback!

Some highlights of…

On behalf of the team, I am pleased to announce that Release Candidate 1 (RC1) of the Spring Cloud Camden Release Train is available today. The release can be found in our Spring Milestone repository. This is mostly a bug fix release as Camden prepares for General Availability (GA). You can check out the Camden release notes for more information.

Notable Changes in the Camden Release Train

Spring Cloud Contract is a new project that provides support for Consumer Driven Contracts and service schemas in Spring applications. Spring Cloud Netflix supports customization of Ribbon component classes via properties, uses the new community maintained OpenFeign and made various fixes and improvements to Zuul. Spring Cloud Consul adds support for Spring Cloud Bus using Consul's event api. The CLI adds a spring cloud…

On behalf of the community, I’m pleased to announce the release of Spring Session 1.3.0.M2. This release release closes lots of community submitted Pull Requests. For a complete list of changes see the changelog.

Note

Spring Session 1.3.0.M1 release had some problems, so we followed up with an immediate release of Spring Session 1.3.0.M2

What’s New in Spring Session 1.3.0 M2

Highlights include:

• First Class Support for Hazelcast

• First class Spring Security’s concurrent session management

• Redis Sample with GenericJackson2JsonRedisSerializer

• spring.session.cleanup.cron.expression can be used to override the cleanup task’s cron expression

• Lots of performance improvements and bug fixes

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We are pleased to announce that Spring Cloud Task 1.0.3.RELEASE and 1.1.0.M1 are now available via Maven Central, Github and the Pivotal download repository. Many thanks to all of those who contributed to this release.

What's new in Spring Cloud Task 1.0.3.RELEASE

1.0.3.RELEASE represents the next minor release for the 1.0.x branch. It's a minor update that cleans up the dependency management within the project to be in alignment with how the rest of the Spring Cloud portfolio manages it's dependencies.

What's new in Spring Cloud Task 1.1.0.M1

Spring Cloud Task 1.1.0's main theme is to…

I am pleased to announce that the second milestone for Spring for Apache Kafka version 1.1.0.M2 is now available in the spring milestone repo.

This includes some bug fixes and the following new features:

• The ability to process a batch of messages (introduced in the last milestone) is now available when using the @KafkaListener annotation, for example…​

  @KafkaListener(id = "list", topics = "myTopic", containerFactory = "batchFactory") public void listen(List list) { ... }

• You can now perform seek operations from the listener - this allows setting an initial offset when partitions are assigned by Kafka when using group management. You can also perform arbitrary seek operations after initialization.

…