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Spring Cloud Task 2.0.0.M3 is now available

We are pleased to announce that Spring Cloud Task 2.0.0.M3 is now available on Github and the Pivotal download repository. Many thanks to all of those who contributed to this release.

What’s new?

This release includes upgrades to existing dependencies as well as some exciting new features for users of Spring Cloud Task. From a dependencies perspective, Spring Cloud Task 2.0.0.M3 has been upgraded to use the Spring Boot 2.0.0.RC1 stack as well as Spring Cloud’s Finchley M6 dependencies.

Beyond just a dependency upgrade, there are a number of new features within Spring Cloud Task 2.0.0.M3. Let’s take a look.

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Spring Integration for AWS 2.0.0.M1 and Spring Cloud Stream Kinesis Binder 1.0.0.M1

Dear Spring Community!

It’s my pleasure to announce two Spring Milestone releases for Amazon Web Services: Spring Integration for AWS 2.0.0.M1 and Spring Cloud Stream Binder for AWS Kinesis 1.0.0.M1.

Both milestones are available in the Spring Milestone repository and they can be consumed as maven dependencies:

<dependency>
    <groupId>org.springframework.integration</groupId>
    <artifactId>spring-integration-aws</artifactId>
    <version>2.0.0.M1</version>
</dependency>

<dependency>
    <groupId>org.springframework.cloud</groupId>
    <artifactId>spring-cloud-stream-binder-kinesis</artifactId>
    <version>1.0.0.M1</version>
</dependency>
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Spring Cloud Finchley M6 is available

On behalf of the community, I am pleased to announce that the Milestone 6 (M6) of the Spring Cloud Finchley Release Train is available today. The release can be found in the Spring Milestone repository. You can check out the Finchley release notes for more information.

Notable Changes in the Finchley Release Train

Finchley.M6 is compatible with Spring Boot RC1. Many updates have been made for compatibility with RC1.

Spring Cloud Sleuth

The internals of Spring Cloud Sleuth were rewritten to use Brave. Please see the Migration Guide for more information.

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Spring Session 1.3.2 Released

This post was authored by Vedran Pavić

On behalf of the community I’m pleased to announce the release of Spring Session 1.3.2.RELEASE. This maintenance release contains numerous bug fixes and improvements.

Some of the highlights include:

  • #951 - SessionRepositoryFilter#changeSessionId does not copy the previous maxInactiveInterval into the new session

  • #983 - Optimize HazelcastSessionRepository write operations

  • #984 - Improve session event handling

You can find the complete details of the release in the changelog.

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Spring Cloud Edgware.SR2 Released

On behalf of the community, I am pleased to announce that the Service Release 2 (SR2) of the Spring Cloud Edgware Release Train is available today. The release can be found in Maven Central. You can check out the Edgware release notes for more information.

Notable Changes in the Edgware Release Train

Spring Cloud Commons

Issues

Spring Cloud Contract

Issues

Spring Cloud Config

Issues

Spring Cloud Consul

Issues

Spring Cloud Netflix

Issues

Spring Cloud Bus

Issues

Spring Cloud Sleuth

Issues

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

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Spring Cloud for Google Cloud Platform 1.0 Milestone 2 Available

Dear Spring Community!

It’s my pleasure to announce today a new project in the Spring Cloud family. It’s called Spring Cloud GCP and its goal is to bring into your applications well-known Spring patterns and Spring Boot conventions for consuming Google Cloud Platform services.

The project currently is in version 1.0.0.M2 and is available from the Spring Milestone Repository:

<dependencyManagement>
   <dependencies>
       <dependency>
           <groupId>org.springframework.cloud</groupId>
           <artifactId>spring-cloud-gcp-dependencies</artifactId>
           <version>1.0.0.M2</version>
           <type>pom</type>
           <scope>import</scope>
       </dependency>
   </dependencies>
</dependencyManagement>
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Spring Data Lovelace M1 released.

On behalf of the Spring Data team I’m happy to announce the first milestone of the Lovelace release train. The release ships over 200 tickets fixed! The most important new features are:

  • JPA 2.2 result streaming.
  • MongoDB Validator and JsonSchema support.
  • Support for MongoDB Change Streams.
  • Neo4J OGM 3.1 upgrade.
  • Exist/Count projections as well as a fluent template API in Spring Data for Apache Cassandra.
  • Spring Data for Apache Geode added JCache Annotation support.
  • Query By Example for Redis repository abstractions.
  • Spring Data REST offers more fine grained method exposure mechanisms.
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Spring Cloud Skipper 1.0 GA Released

On behalf of the team, I am pleased to announce the release of Spring Cloud Skipper 1.0 GA

Skipper is a lightweight tool that allows you to discover Spring Boot applications and manage their lifecycle on multiple Cloud Platforms. You can use Skipper standalone or integrate it with Continuous Integration pipelines to help implement the practice of Continuous Deployment.

The getting started section in the reference guide is the best place to start kicking the tires.

Release Highlights:

  • Introduction of Flyway to manage schema along with various schema tweaks.

  • Option to delete a release along with its package.

  • Refined the REST API.

  • Updated properties to YAML converter.

  • Add resource metadata in manifest template.

  • Separate platform deployers into multiple maven modules.

  • Support passing to the shell commands to execute.

  • Updated documentation.

  • Various bug fixes.

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Spring Cloud Data Flow 1.3 GA released

On behalf of the team, I am pleased to announce the general availability of Spring Cloud Data Flow 1.3 across a range of platforms

Follow the Getting Started guides for Local Server, Cloud Foundry, and Kubernetes

Release Highlights

Stream updates and rollback

A streaming data pipeline orchestrated as a series of microservice applications has always been the core value of Spring Cloud Data Flow’s design. In Data Flow 1.3 we have provided the ability to update sources, processors, and sinks independently without having to undeploy and redeploy the entire stream.

The stream update and rollback functionality is implemented by delegating the deployment process to a new Spring Cloud project called Skipper. Skipper is a lightweight Spring Boot application, purpose-built to fill this feature gap in Data Flow. Skipper defines a package format, much like helm or brew and can also deploy/undeploy applications to multiple cloud platforms: Local, Cloud Foundry, and Kubernetes. It uses the same Spring Cloud Deployer libraries that have been part of Data Flow since the beginning. Recent presentations at SpringOne 2017 introduces Skipper and the integration with Data Flow in more depth.

When deploying a Stream, Data Flow creates Skipper package describing the Stream and the applications that are part of the Stream definition. Skipper then deploys the applications to the desired platform. When requesting a stream update, only the application or applications that need to be changed are automatically redeployed. A simple strategy managed by a Spring Statemachine instance performs the update or rollback steps.

Data Flow includes new stream commands to make upgrade and rollback operations.

dataflow:>app register --name transform --type processor --uri maven://com.eg:transformer:0.0.1

dataflow:>stream create mystream --definition "jdbc | transform | mongodb"

dataflow:>app register --name transform --type processor --uri maven://com.eg:transformer:0.0.2

dataflow:>stream update mystream --properties “version.transform=0.0.2”

dataflow:>stream rollback mystream

In this series of commands, the stream is deployed using version 0.0.1 of the transformer. The jdbc and mongodb source and sink are already registered. The stream is then updated to use version 0.0.2 of the transformer. Only the transform application is updated, with version 0.0.2 being deployed and version 0.0.1 being undeployed. The jdbc and mongodb applications are left as-is. The rollback command does the opposite, bringing the stream back to the state with version 0.0.1 of the transformer.

Note: To use Data Flow and Skipper, Data Flow’s feature toggle for Skipper must be enabled in both the Data Flow Server and shell.

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