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Reactor Aluminium-SR1 has landed

A batch update of releases has arrived and it is brought to you with the new Aluminium-SR1 Bill Of Material. Just in time for Spring Framework M5 !

Reactor-Core 3.0.5

release notes

An important quality update with new features including predicated-based windows and the checkpoint operator, fixes, test coverage and for the first time in 3.0.x line, a draft reference guide.

We are now working on 3.0.6.RELEASE which is going to be our last major 3.0 content update before 3.1.0.RELEASE. We encourage our Spring Community to just follow deprecated instructions if they hit any of the @Deprecated API, thus simply preparing for a quick, painless, upgrade when time comes. Have a look at our issues backlog for a more detailed scope.

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This Week in Spring - February 21st, 2017

Welcome to another installment of This Week in Spring! This week I’m in Atlanta, GA for the incredible DevNexus event and then it’s off to Geneva, Switzerland for the Voxxed CERN event. As usual, don’t hesitate to say “Hi” if you’re around!

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Spring IO Platform Brussels-RELEASE

It’s my pleasure to announce that Spring IO Platform Brussels-RELEASE is available now from the Spring release repository and Maven Central.

The Brussels release introduces the following projects to the Platform:

  • Spring Kafka 1.1

The Brussels release also upgrades the versions of a number of projects:

  • Spring AMQP 1.7
  • Spring Boot 1.5
  • Spring Data Ingalls
  • Spring Integration Java DSL 1.2
  • Spring Integration Kafka 2.1
  • Spring LDAP 2.3
  • Spring Security 4.2
  • Spring Session 1.3
  • Spring Web Services 2.4

The versions of numerous third-party dependencies have also been updated.

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Spring Cloud Data Flow 1.2 M1 released

On behalf of the team, I am excited to announce the release of the first milestone of Spring Cloud Data Flow 1.2.

Note: A great way to start using this new release(s) is to follow the release matrix on the project page, which includes the download coordinates and the links to the reference guide.

Over the last few weeks, we have added new features and improvements to the overall orchestration of data microservices. The following new features were included in the 1.2.0.M1 release:

Core

  • Introduce dedicated prefixes for deployment properties. Using the deployer properties is as simple as deployer.<appname>.xxx as opposed to app.<appname>.spring.cloud.deployer.xxx
  • Introduce a new REST-API controller and shell support to cleanup Task Executions
  • Foundation work to consolidate the use of controllers between Task deployments and Task Executions
  • Consolidate REST-API call traces and return codes for consistency
  • Adds role-based access control to define who has access to create, deploy, destroy, or view streams/tasks. This works seamlessly in coordination with the supported authentication methods.
  • Performance optimizations to “stream list” operation. Instead of making individual calls for each app associated with the stream, the newly introduced MultiStateAppDeployer SPI operation invokes a call per stream that queries all the application statuses in a single network call
  • Improves error reporting for “stream list” operation
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This Week in Spring - February 14th, 2017

Welcome to another installment of This Week in Spring! It’s Valentines Day for some, and so happy Valentines day to you! This week I’m in Memphis, Tennessee for business and then it’s off to Saint Louis where I’ll be presenting on Reactive Spring with my buddy Mark Heckler (join us!), then it’s off to Atlanta, Georgia, ahead of next week’s big DevNexus show. Check out what Pivotal is up to at the event!

As usual, we’ve got a lot to cover so let’s get going!

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SpringOne Platform 2016 Replay: Spring Data Hazelcast: Fluently Accessing Distributed Repositories

Recorded at SpringOne Platform 2016.
Speaker: Victor Gamov, Neil Stevenson, Hazelcast
Slides: http://www.slideshare.net/SpringCentral/spring-data-hazelcast-fluently-accessing-distributed-repositories

The primary goal of the Spring Data project is to make it easier to build Spring-powered applications that use data access technologies.

In this talk, Neil and Viktor will present using a new Spring Data for Hazelcast project and demonstrate how using the Spring Data paradigm gains the power of a distributed data repository.

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SpringOne Platform 2016 Replay: Streaming Live Data and the Hadoop Ecosystem

Recorded at SpringOne Platform 2016.
Slides: http://www.slideshare.net/SpringCentral/streaming-live-data-and-the-hadoop-ecosystem

It’s not always easy to get the data you need for analysis. And it becomes even more challenging if it is live streaming data you are working with. Learn how you can make Hadoop work for you in the most effective way possible, especially when it comes to adapting to the agile business requirements of today’s competitive environment. We will cover the Hadoop ecosystem – what is Hadoop, HDFS, MapReduce, Yarn, and then how leading open source projects such as Hive, Ambari, Ranger, Atlas, NiFi interact and integrate to support the variety of data used for analytics today.

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SpringOne Platform 2016 Replay: Spring with ApacheNiFi

Recorded at SpringOne Platform 2016.
Speaker: Oleg Zhurakousky
Slides: http://www.slideshare.net/SpringCentral/spring-with-apachenifi

Spring Integration has long captured the hearts and minds of the developers world wide for its emphasis on simplicity, modularity and productivity when it comes to all things related to work-flow orchestration and complex event processing and is successfully used in a variety of Big Data solutions. Apache NiFi, on the other hand, is a new addition to the already rich Big Data technology stack.

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