It is my pleasure to announce that the Spring AMQP 1.6.1 maintenance release is available now.

As usual, thanks to the community for any feedback and contribution all the ways!

This release contains several critical bug fixes, therefore an upgrade is highly recommended.

We haven’t switched master branch to 2.0 yet, but that is really our intention in the nearest future to start enjoying a new Spring 5.0 and Java 8 foundation for Spring AMQP project code base!

Project Page | GitHub | Help | Documentation

We are pleased to announce the release of Spring Cloud Data Flow's Kubernetes 1.0.0.RELEASE.

Spring Cloud Data Flow for Kubernetes provides support for orchestrating long-running (streaming) and short-lived (task/batch) data microservices on Kubernetes.

This project was originally conceptualized by the community and we are thankful to Florian Rosenberg for his early contributions that eventually made it into the official Spring Cloud Deployer for Kubernetes project. Building upon this theme, we recently bumped into Donovan Muller's blog, where he walks through his experience extending the…

We are pleased to announce the release of Spring Cloud Data Flow’s Cloud Foundry 1.0.0.M4.

In this milestone release, we have few improvements to the APIs and the general stability of the overall design constructs.

• Builds upon 1.0.0.RELEASE of Spring Cloud Data Flow Core (shell, UI, REST-APIs, etc.)

• Streamlines application vs. deployment property semantics

• Adds a migration guide and other documentation fragments to the reference documentation

• Adds a project site

Journey Ahead

• We are looking forward to Reactor and Cloud Foundry Java Client’s RC and GA releases and by this month, we shall release 1.0.0.RELEASE of Spring Cloud Data Flow for Cloud Foundry.

• We have exciting work-in-progress to orchestrate short-lived microservices through TaskLauncher constructs in the Spring Cloud Deployer for Cloud Foundry project. We are hopeful to deliver the BETA release of this functionality alongside the upcoming Pivotal Cloud Foundry’s 1.7.x release.

…

On behalf of the team, I’m excited to announce the 1.0 GA release of Spring Cloud Data Flow!

Note

A great way to start using this new release is to follow the Getting Started section of the reference documentation. It uses a Data Flow server that runs on your computer and deploys a new process for each application.

Spring Cloud Data Flow (SCDF) is an orchestration service for data microservices on modern runtimes. SCDF lets you describe data pipelines that can either be composed of long lived streaming applications or short lived task applications and then deploys these to platform runtimes that you may already be using today, such as Cloud Foundry, Apache YARN, Apache Mesos, and Kubernetes. We provide a wide range of stream and task…

We are pleased to announce the release of Spring Cloud Data Flow for Apache YARN 1.0.0.RELEASE.

Spring Cloud Data Flow for Apache YARN provides support for orchestrating long-running (streaming) and short-lived (task/batch) data microservices on Apache YARN.

This project was originally conceptualized with the goal to supplement the existing Spring XD users who have investments running streaming and batch data pipelines in a more traditional bare-metal setup. We wanted to provide migration path to help port over their existing investments and the tools and techniques to reap the benefits of…

Welcome to another installment of This Week in Spring! This week I'm in Dublin, Ireland and London, UK, and Boston, Massachusetts, giving open workshops at Pivotal Dublin and London and speaking to local customers. It's been a fun week and there's a lot to cover! So, let's get to it!

This is my favorite time of year! As we lead to SpringOne Platform, there's so much good stuff being released that one can hardly keep up! I am really looking forward to this year's SpringOne Platform show, coming in early August. It's an amazing time to build applications, and SpringOne Platform is in a unique…

It is my pleasure to announce that the Spring for Apache Kafka 1.0.2 maintenance release is available now.

As usual, thanks to the community for any feedback and contribution all the ways!

This release contains several critical bug fixes, therefore an upgrade is highly recommended. The master branch has now switched to 1.1 and we are starting migrating to Kafka 0.10 and other features on the matter with possible Milestone 1 later this month.

Project Page | GitHub | Help | Documentation

For more details about Spring for Apache Kafka , check Gary Russell’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…

On behalf of the team, I am pleased to announce that Service Release 3 of the Spring Cloud Brixton Release Train is available today. The release can be found in our Spring Release repository and Maven Central.

Included in this release is the GA release of Spring Cloud Task.

Other than the addition of Spring Cloud Task, this release includes primarily bug fixes.

The following modules were updated as part of Brixton.SR3:

• Spring Cloud Security 1.1.2.RELEASE
• Spring Cloud Netflix 1.1.4.RELEASE
• Spring Cloud Sleuth 1.0.3.RELEASE
• Spring Cloud Task 1.0.1.RELEASE

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

We are pleased to announce the release of Spring Cloud Task 1.0.1.RELEASE. This is the recommended GA release for Spring Cloud Task and is available from Maven Central as well as the usual other locations.

How did we get here?

Spring Cloud Task, is a step in an evolution of data applications in the Spring portfolio. As we announce this release, it may be helpful to look at how we got to this point.

It began with Spring Batch

Built upon the Spring portfolio, the evolution of this type of finite workload really began with Spring Batch. One of the main workload specific extensions of the Spring framework, Spring Batch provided functionality for performing finite amounts of processing in an enterprise friendly way. With multiple processing models (Tasklet vs Chunk) as well as scalability options that allowed for…