This Week in Spring - June 7th, 2016

Welcome to another installment of This Week in Spring! It’s already June! Where. Does. The. Time. GO?? This week I’m in Chicago, IL, for the Chicago Coder Conference, Boston and New Hampshire for customer visits, London, England for Devoxx UK and Talin, Estonia for Geekout EE. If you’re around be sure to say hi! Now then, we’ve got a lot to cover this week so let’s get to it!


Introducing Spring Cloud Cloud Foundry Service Broker

I am pleased to announce the newest addition to the Spring Cloud family. Spring Cloud Cloud Foundry Service Broker is a framework for building service brokers for the Cloud Foundry platform.

Cloud Foundry service brokers

Service brokers provide a means to extend Cloud Foundry with managed services that can be consumed by applications deployed to the platform. Managed services typically expose some sort of resource to an application, such as a database or other persistent store, a messaging system, or other supporting infrastructure. Service brokers publish a catalog of services and service plans, manage the provisioning and de-provisioning of service instances, and provide connection details and credentials for an application to consume the resource. Service brokers are registered to Cloud Foundry and communicate with the platform using a well-defined Service Broker REST API.

Spring Cloud Cloud Foundry Service Broker implements the full service broker REST API as Spring MVC endpoints. This allows a service broker author to focus on the logic necessary to manage the backing resources without having to worry about implementing the broker API semantics.


Notes on Reactive Programming Part I: The Reactive Landscape

Reactive Programming is interesting (again) and there is a lot of noise about it at the moment, not all of which is very easy to understand for an outsider and simple enterprise Java developer, such as the author. This article (the first in a series) might help to clarify your understanding of what the fuss is about. The approach is as concrete as possible, and there is no mention of "denotational semantics". If you are looking for a more academic approach and loads of code samples in Haskell, the internet is full of them, but you probably don’t want to be here.


Spring Integration Kafka Support 2.0.0 Release Candidate is now available

I am pleased to announce that the spring-integration-kafka (Spring Integration Kafka Support) Release Candidate for version 2.0 is now available.

The artifact org.springframework.integration:spring-integration-kafka:2.0.0.RC1 is available in the Milestone Repository.

This version is based on the just released Spring for Apache Kafka release candidate 1.0.0.RC1.

There are not many changes since the previous Milestone 1. Just some general internal fixes and upgrades to accommodate recent Spring for Apache Kafka changes.


Spring for Apache Kafka 1.0 Release Candidate 1 Available

On behalf of the Spring Integration and Spring Cloud Stream teams, I’m pleased to announce that the spring-kafka (Spring for Apache Kafka) Release Candidate for version 1.0 is now available.

The artifacts org.springframework.kafka:spring-kafka:1.0.0.RC1 and org.springframework.kafka:spring-kafka-test:1.0.0.RC1 are available in the Milestone repository.

First of all many thanks to everyone involved, to active community members, who provided feature requests and contributions. Special thanks to Martin Dam, who spent a lot of time helping us with the pause/resume algorithm to handle slow listeners.