Hi, Spring fans! Welcome to another installment of This Week in Spring! Today I just wrapped up my appearance in Brisbane, Australia, where I have been for the epic YOW! conference. Truly, one of my all-time favorite shows on the planet. I feel like an imposter in the ranks of the other speakers. I can not recommend this show enough.

I'm just about to board my fight back to San Francisco, and we've got a ton of stuff to get to so let's press on!

• Spring Cloud Data Flow 2.3.0 GA Released
• Stream Processing with Spring Cloud Stream and Apache Kafka Streams. Part 6 - State Stores and Interactive Queries
• Stream Processing with Spring Cloud Stream and Apache Kafka Streams. Part 5 - Application Customizations
• Spring Data R2DBC goes GA
• Spring Boot 2.2.2 is now available
• Spring Boot 2.1.11 is now available
• In last week's A Bootiful Podcast, I talked to Pivotal's Katrina Bakas about the Pivotal HealthWatch product, Kubernetes, Cloud Foundry and so much more.
• …

With the recent release of Spring Boot 2.2, we'd like to announce that maintenance for Spring Boot 2.1 will end on November 1st 2020.

We'll keep publishing the occasional maintenance release up until that point, but we recommend that all users consider upgrading to Spring Boot 2.2 as soon as possible. Upgrading to Spring Boot 2.2 from 2.1 should not be too difficult, and upgrade instructions are available on the WIKI.

In order to help track the state of supported releases we've also introduced a new "supported versions" WIKI page. You can see at a glance which Spring Boot versions are…

The release 2.3.0 delivers a lot of enhancements and generic compatibility changes for Spring Boot 2.2.x and Spring Cloud Hoxton.

Continuous Deployment For Tasks

As task applications evolve faster to keep up with business needs, the ability for new versions to be consumed via Data Flow in an automated way is needed. While Data Flow has supported the ability to register multiple versions of a task application in previous iterations, the ability to run them in a practical way by re-hydrating command line arguments, deployment properties, and application properties used in previous executions has…

Part 1 - Programming Model Part 2 - Programming Model Continued Part 3 - Data deserialization and serialization Part 4 - Error Handling Part 5 - Application Customizations

In this part (the sixth and final one of this series), we are going to look into the ways Spring Cloud Stream Binder for Kafka Streams supports state stores and interactive queries in Kafka Streams.

Named State Stores

When you have the need to maintain state in the application, Kafka Streams lets you materialize that state information into a named state store. There are several operations in Kafka Streams that require it to keep track of the state such as count, aggregate, reduce, various windowing operations, and others. Kafka Streams uses a special database called RocksDB for maintaining this state store in most cases (unless you explicitly change…

On behalf of the team and everyone who has contributed, I'm happy to announce that Spring Boot 2.1.11 has been released and is now available from repo.spring.io and Maven Central.

This release includes 53 fixes, improvements, and dependency upgrades. Thanks to all those who have contributed with issue reports and pull requests.

How can you help?

If you're interested in helping out, check out the "ideal for contribution" tag in the issue repository. If you have general questions, please ask on stackoverflow.com using the spring-boot tag or chat with the community on Gitter.

Project Page | GitHub | Issues | Documentation | Stack Overflow | …

On behalf of the team and everyone who has contributed, I'm happy to announce that Spring Boot 2.2.2 has been released and is now available from repo.spring.io and Maven Central.

This release includes 88 fixes, improvements, and dependency upgrades. Thanks to all those who have contributed with issue reports and pull requests.

How can you help?

If you're interested in helping out, check out the "ideal for contribution" tag in the issue repository. If you have general questions, please ask on stackoverflow.com using the spring-boot tag or chat with the community on Gitter.

Project Page | GitHub | Issues | Documentation | Stack Overflow | …

On behalf of the team and everyone that contributed, I am delighted to announce that Spring Data R2DBC 1.0 is generally available from repo.spring.io as well as Maven Central!

Spring Data R2DBC 1.0 is a non-blocking database client library for the just released R2DBC specification that lets you build reactive applications that use SQL databases. The most notable features of Spring Data R2DBC are:

• Functional-reactive declaration of data access
• Fluent API
• Support for Transactions
• Named parameter support (Dialect-aware)
• Repositories
• Kotlin Coroutines extensions

Spring Data R2DBC 1.0 requires JDK 8 or higher and any R2DBC driver. Head over to start.spring.io and add R2DBC to configure your dependencies or, if you're already using the Spring Boot R2DBC starter, upgrade your spring-boot-bom-r2dbc to 0.1.0.M3…

Part 1 - Programming Model Part 2 - Programming Model Continued Part 3 - Data deserialization and serialization Part 4 - Error Handling

In this blog post, we continue our discussion on the support for Kafka Streams in Spring Cloud Stream. We are going to elaborate on the ways in which you can customize a Kafka Streams application.

Customizing the StreamsBuilderFactoryBean

Kafka Streams binder uses the StreamsBuilderFactoryBean, provided by the Spring for Apache Kafka project, to build the StreamsBuilder object that is the foundation for a Kafka Streams application. This factory bean is a Spring lifecycle bean. Oftentimes, this factory bean must be customized before it is started, for various reasons. As described in the previous blog post on error handling, you need to customize the StreamsBuilderFactoryBean…

Part 1 - Programming Model Part 2 - Programming Model Continued Part 3 - Data deserialization and serialization

Continuing with the series on looking at the Spring Cloud Stream binder for Kafka Streams, in this blog post, we are looking at the various error-handling strategies that are available in the Kafka Streams binder.

The error handling in Kafka Streams is largely centered around errors that occur during deserialization on the inbound and during production on the outbound.

Handling Deserialization Exceptions

Kafka Streams lets you register deserialization exception handlers. The default behavior is that, when you have a deserialization exception, it logs that error and fails the application (LogAndFailExceptionHandler). It also lets you log and skip the record and continue the application (LogAndContinueExceptionHandler). Normally, you provide the corresponding…