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The evolution of Spring Fu

I take the opportunity of a short stop between SpringOne platform where I gave the first talk about Spring Fu and Kotlinconf to give an overview of the evolution of this project, summarize the current status and share what could be the next steps.

Early June, I announced a new experimental project named Spring Fu, with the goal to experiment on a new kind of API to configure Spring applications using Kotlin DSL and functional configuration.

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Spring Vault 2.1 GA released

On behalf of the community, I’d like to announce the general availability of Spring Vault 2.1. Spring Vault 2.1 requires JDK 8 or higher and specifically supports JDK 11 as the next long-term support release. The most notable changes of Spring Vault 2.1 are:

  • Extending infrastructure-based authentication to support Google Cloud IAM and Azure Managed Service Identity.
  • Integrating Vault’s versioned Key-Value backend.
  • Wrapping API support.
  • Java 11 compatibility.

This release is compatible with Vault versions from 0.5.2 up to 0.11.1.

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What's new in Spring Data Lovelace?

With Spring Data Lovelace just released in its generally available version last week, it is time to have a brief walk through the new features we have added. The release train is pretty packed with features. In this blog post, I cover the more general ones. Advanced, store-specific news is covered in the following blog posts:

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What's new in Spring Data Lovelace for MongoDB?

The past year has seen a lot of enhancements brought to the NoSQL Store including a bunch of new features and extended capabilities. We collaborated closely with the driver team at MongoDB, so the release already ships with decent support for sessions, change streams, schema validation, and (of course) transactions.

The most interesting new feature is probably MongoDB 4.0’s support for Multi-Document Transactions. If you have followed this blog before, you have probably read our Hands on Guide that explains both ClientSessions (which are the main building block) and transactions themselves. In short, SpringData provides you with everything you need to leverage Spring managed transaction support in your project. To use it, declare MongoTransactionManager in your configuration, as the following example shows:

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The Reactive Revolution at SpringOne Platform 2018 (part 1/N)

Hi Spring fans! What a crazy week in Spring it’s been! I’m at SpringOne Platform 2018 soaking up all the exciting community events, interacting with people from around the planet who love Pivotal and love Spring! I just got asked to take a selfie with a woman from Vietnam while five miles from the show - at a local mall where I happened to be for a community dinner! It’s wonderful that the Pivotal brings people of so many disparate cultures and places together.

Today, Wednesday 26th, 2018, was a doozie! There are so many wonderful things happening this week, of course, but today was a very special one for me. Today saw us take the wraps off of the amazing work Pivotal is doing on two fronts. I wanted only to briefly touch on these topics in this post. You’ll no doubt hear more about this from us in the weeks to come!

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Spring Batch 4.1.0.RC1 is now available

On behalf of the Spring Batch team, I’m pleased to announce that Spring Batch 4.1.0.RC1 is now available on Github and the Pivotal download repository.

What’s new?

In this release, we worked mainly on making Spring Batch build and run correctly on Java 8, 9, 10 and 11! This release is based on Spring Framework 5.1 GA as well as the latest versions of Spring Integration, Spring AMQP and Spring Data. For a complete list of changes, please refer to the change log.

What’s next?

Our plan is to release Spring Batch 4.1 GA by the end of October right in time for Spring Boot 2.1 GA. The focus will be on making this release candidate as stable as possible so please help us by testing new features and submitting your feedback on JIRA, StackOverflow or Gitter. You can consume Spring Batch 4.1.0.RC1 with Spring Boot 2.1.0.M4.

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What's new in Spring Data Lovelace for Redis and Apache Cassandra?

This blog post explains the new and noteworthy in Spring Data Lovelace for Apache Cassandra and Redis. Make sure to also check out the blog post on What’s new in Spring Data Lovelace for MongoDB?.

With Spring Data Lovelace just released in its generally available version last week, it’s time to have a brief walk through the new feature’s we have added. The release train is pretty packed with features.

In this blog post, I’ll be covering Apache Cassandra and Redis.

Spring Data for Apache Cassandra

With this release, we refined data access with Cassandra-specific types, introduced support for lifecycle events, improved the programming experience for both Java and Kotlin usage and included various other refinements. Let us take a look at how this release can help improve your data access to Cassandra.

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This Week in Spring (SpringOne Platform 2018 edition) - September 25th, 2018

It’s been such a crazy SpringOne Platform 2018 and we literally just started! I don’t even know where to begin! The show represents the convergence of the best and the brightest in the ecosystem. It’s absolutely amazing all the people who want and love to be here.

From our friends in the ecosystem, we see people from all organizations. IBM, Amazon Web Services, Microsoft and Google are all here hoping to make their platform the most compelling place to run Pivotal Cloud Foundry and Spring-based workloads. It’s great to see my friends from all these organizations! Friends like my friends Erin Schnabel, Emma Tucker, Billy Korando and Pratik Patel from IBM…

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Spring Cloud Function 2.0 and Azure Functions

Spring Cloud Function has had support for Microsoft Azure Functions since version 1.0, but in the latest 2.0 releases (still in milestone phase) we decided to change the programming model a bit. This article describes what the changes mean for users, and provides a bit of background behind the shift. We in the Spring team had a lot of fun working on this and collaborating with the folks at Microsoft to get the best blend of the two technologies for our users.

Azure Functions for Java

Microsoft has had Java support in Azure Functions for a while, and it enables developers to easily write and deploy Java code that connects in a serverless way to a wide range of platform services (events, databases, storage, HTTP gateways, etc.) in Azure. It comes with an annotation-based programming model that puts the function implementations in Java methods. So you write a method and annotation it with @FunctionName, and it becomes an Azure Function. There is a rich set of tools based on a Maven plugin (currently) that drives the Azure command line and can be used to build a function, run and debug it locally and deploy it to the cloud. There is a Quickstart Guide on the Azure website which will help you get all the pre-requisites installed and working, and there is more detailed documentation about how Azure Functions works in the Developer’s Guide.

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