Spring Boot 1.4.6 includes 70 fixes and a selection of improvements and dependency upgrades. Thanks to all that have contributed!
The Spring Blog
On behalf of the Spring Cloud team it is my pleasure to announce a new milestone release of Spring Cloud Pipelines -
We are pleased to announce that Spring Cloud Task 1.2.0.RC1 is now available via Github and the Pivotal download repository. Many thanks to all of those who contributed to this release.
- Upgrade to Spring Cloud Stream Chelsea GA.
closecontext.enabledas to match the Spring Boot style for enabled properties.
- Task name can be set when creating a
TaskExecutionexternally, allowing the launcher to set the name in a persistent manor.
OrderedInterface to Task Events and Batch Job Events so the user can establish when task or batch events are emitted from their Spring Cloud Task application.
- Cleaned up Spring Cloud Task dependencies.
- Update default task name creation to prevent conflicts with JMX.
On behalf of the community, I am happy to announce the general availability of the Spring Cloud Stream Chelsea release train. For this release train, the first general availability release is Chelsea.SR1, which fixes a number of issues over Chelsea.RELEASE (all within the scope of the metrics export feature). Chelsea.SR1 is also included as part of Spring Cloud Dalston.RELEASE.
The new release is available in Maven Central, and a detailed description of its features can be found in the reference documentation. For information about artifacts and most recent changes, please consult the release notes, as follows:
On behalf of the Spring Data team, I’d like to announce the availability of the second milestone of the release train Kay. The release is an important step towards a second generation of Spring Data.
We’ve upgraded the majority of the codebase to Java 8, now also embracing e.g.
Optional in method signatures. This mostly affects internal SPIs but also leaks into user code, especially in
CrudRepository. The support for reactive Spring Data repositories has been extended to Couchbase (Thanks, Subhashni!), the Redis module has a reactive template API now. The release also ships support for
IsNotEmpty for derived queries and implementaitons of those for MongoDB and JPA. The aggregation framework in MongoDB now also supports streaming results.
On behalf of the community, I am pleased to announce that the General Availability (RELEASE) of the Spring Cloud Dalston Release Train is available today. The release can be found in Maven Central. You can check out the Dalston release notes for more information.
Spring Cloud Vault Config is a new project that provides client-side support for externalized secret management in a distributed system via Hashicorp Vault.
Config Server now has support for multiple backends via a Composite pattern. This allows for combinations of backend types that was not possible before, such as: Vault and git or multiple git backends. Authentication to git repositories hosted by AWS Codecommit is now supported. In the previous (Camden) release, Hashicorp Vault was already added as a backend to Config Server to go along with the VCS based backends.
On behalf of the community, it’s my pleasure to announce the general availability of Spring Vault 1.0 – the very first GA release of Spring Vault after almost a year of development.
The artifacts are available from Maven Central and Bintray.
<dependency> <groupId>org.springframework.vault</groupId> <artifactId>spring-vault-core</artifactId> <version>1.0.0.RELEASE</version> </dependency>
The release ships more than 50 tickets fixed in total. Here’s a very truncated list of the most important features shipping with the release:
We are pleased to announce that these maintenance releases of Spring for Apache Kafka are now available, 1.2.0.RELEASE and 1.1.4.RELEASE.
These versions include several bug fixes and improvements, as well as introduce support for KStreams.
They are functionally equivalent; the 1.2.0.RELEASE is based on the 0.10.2.0
kafka-clients jar and 1.1.4.RELEASE can be used with 0.10.0.x and 0.10.1.x.
While 1.1.4.RELEASE will work at runtime with a 0.10.2.x client library, some breaking changes in the embedded kafka API means that the embedded kafka Junit
spring-kafka-test will not work and 1.2.0.RELEASE is required for that.
The Spring Integration team is pleased to announce that the third milestone for the Spring Integration 5.0 release (
5.0.0.M3) is now available.
Initial implementation for a Spring Integration Testing Framework - the
@SpringIntegrationTestannotation for test classes and
MockIntegrationfactory help you to write unit tests for integration flows and channel adapters. We intend to flush out this capability with more features before GA, including more mocking, verifications and some
send-and-receiveutilities to test components in isolation. Feedback is welcome!
POJO handler method invocations (
@Transformeretc., or such methods invoked from XML definitions) now use
InvocableHandlerMethodby default. Together with the
@Defaultutilities that allows us to implement conditional method invocation scenarios based on the Content-Type and target method arguments resolution. To restore the previous SpEL-based behavior, the
@UseSpelInvokermethod-level annotation is provided.
A based on the WebFlux
ReactiveHttpRequestExecutingMessageHandlerimplementation is provided. Together with a
outputChanneloptions it provides backpressure manner for remote HTTP service consumption.
The (S)FTP (and AWS S3) Inbound Channel Adapters can now restore file tree locally. For that purpose a new,
RecursiveDirectoryScanneris introduced. The
useWatchServiceoption is also provided.
Web Services Gateways now can exchange
WebServiceMessages directly as the inbound/outbound
payload. This allows the support of MTOM via direct access to
UnmarshallingTransformercan now process a
MimeMessageas the payload to unmarshal it into an object graph with attachments.
The reply producing
MessageHandlernow has a fallback to the
replyChannelheader from the reply message, if there is no
replyChannelin the request message headers. This allows the implementation of business process-like scenarios when the next step is determined by the result of current calculations.