Whew! What a week! I'm exhausted! I've been running around visting one customer after another this week and it's only Tuesday! My brain is still a smoldering hole from the craziness of last week's epic SpringOne Platform 2018 event in Washington DC, and needless to say there's a ton of new things to investigate and tons of videos to be available to the audience soon. This week is a wee bit more tame, so without further ado, let's get to it!

I don't know where you are in the world as you read this but I hope you'll join me 17:00 BST, for my appearance at the vJUG where I'll be looking at Bootiful Testing…

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:

• Jens Schauder introducing Spring Data JDBC

• Jens again on how to model aggregates with Spring Data JDBC

• Christoph Strobl on MongoDB

• Mark Paluch on Spring Data for Apache Cassandra & Redis

Read up on those? Alright, then let’s get started on the more general items…

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…

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…

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…

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…

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…

Spring Vault 2.1 is already in sight. I would like to use this post to take a deeper look at the changes and features that are in the upcoming release.

The team has been working on a whole bunch of new features:

• 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

Spring Vault supports HashiCorp Vault versions 0.5 up to 0.11. You can find the Spring Vault and Spring Cloud Vault examples repository on GitHub. Now, let’s dive into the Spring…

In my previous blog article, I described how to set up and use Spring Data JDBC. I also described the premise of making Spring Data JDBC easier to understand than JPA. This becomes interesting once you consider references. As a first example, consider the following domain model:

class PurchaseOrder {

  private @Id Long id;
  private String shippingAddress;
  private Set<OrderItem> items = new HashSet<>();

  void addItem(int quantity, String product) {
    items.add(createOrderItem(quantity, product));
  }

  private OrderItem createOrderItem(int quantity, String product) {

    OrderItem…