Recorded at SpringOne Platform 2016. Speaker: Dr. David Syer Slides: http://www.slideshare.net/SpringCentral/leadership-election-with-spring-cloud-cluster

Leader election allows application to work together with other applications to coordinate a cluster leadership via a third party system. A leader can then be used to provide global state or global ordering, generally without sacrificing availability. In this presentation we show how Spring Cloud Cluster provides a simple abstraction for leader election and how it is implemented using zookeeper, hazelcast and etcd.

Note that 1.0.1 release…

Speaker: Josh Long https://www.twitter.com/starbuxman

Hi Spring fans! In this tip, we'll look at Cloud Foundry, a an open-source cloud platform that's optimized for managing applications. To those of you in the US, happy Thanksgiving tomorrow!

On behalf of the community, I’m pleased to announce the release of Spring Session 1.3.0.RC1. This release release closes lots of community submitted Pull Requests. For a complete list of changes see the changelog.

What’s New in Spring Session 1.3.0 RC1

Highlights include:

• First class Spring Security’s RememberMe Support

• Updated guides to use Lettuce

• OrientDB Support

• Configuration Improvements

• Performance Optimizations

• Bug Fixes

Contributions

Without the community we couldn’t be the successful project we are today. I’d like to thank everyone that created issues & provided feedback…

On behalf of the Spring Cloud Data Flow team, I am pleased to announce the 1.1.0.RC1 release of Spring Cloud Data Flow for Apache YARN.

Spring Cloud Data Flow for Apache YARN allows one to use all the goodness of Spring Cloud Data Flow (like the Shell and UI) while targeting Apache YARN as a backend. Stream components are deployed as individual apps in Apache YARN, leveraging the power of the platform to handle scaling and health monitoring.

This first release candicate

• Builds upon Spring Cloud Data Flow 1.1.0.RC1 and Spring Cloud Deployer 1.1.0.RC1.
• Support for keeping multiple deployer versions in hdfs.
• Preparation of supporting upgrades on Ambari when these become available with Ambari future versions.
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On behalf of the Spring Data team, I’d like to announce the first milestone of the Kay release train. This is a special release train as it's going to ship a new generation of Spring Data that will include a couple of breaking changes going forward.

Infrastructure upgrades

The first and most noticeable change is the upgrade to Java 8 as a minimum baseline (no JDK 6 compatibility anymore) and an upgrade to Spring 5 as framework foundation. In subsequent milestones we're going to ship some significant internal rewrites that will also affect user facing API to make use of the new language…

On behalf of the team, I am pleased to announce the GA release of Spring Cloud Data Flow 1.1. Follow the links in the getting started guide to download the local server implementation and shell to create Stream and Tasks.

General highlights of the 1.1 GA Release include:

• Builds upon Spring Boot 1.4, Spring Cloud Camden SR2, Spring Integration 4.3 and Spring Cloud Task 1.1 release improvements.

• Adds LDAP, Basic and File based backend authentication

• Improvements to OAUTH backed authentication

• LDAP authentication is now supported with SSL

• Adds a form-based login page for non-OAUTH backend authentication methods such as the LDAP, Basic and File-based options

• Adds the ability to pass application specific properties via YAML file. This is particularly useful when deploying streams that require many deployment properties to be set.

• Portable deployment properties for memory, disk and cpu are in place for support across various runtime implementations.

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Welcome to another installment of This Week in Spring! This week I'm.. home! It's Thanksgiving this week here in the states, after all. I am sure that I speak for the entire Pivotal team when I say that we are grateful for you, the most wonderful community on the planet. Thanks so much, and if you're celebrating Thanksgiving, then happy Thanksgiving to you! When you're finished with your meal - barely able to keep an eye open - I hope you'll find a comfy arm chair and take in some of the content in this week's roundup.

• the good Dr. David Syer doesn't always do view templating, but when he does..
• check out this replay of Spring Security lead Rob Winch and ninja Joe Grandja as they look forward to Spring Security 4.1
• continuing our Spring Tips series, last week we looked at Spring Cloud Data Flow as a way to quickly build stream-processing solutions
• Hurray! Congratulations to the Apache Geode project who just saw their project promoted to an Apache top level project
• I really liked this post from Spring Cloud ninja Ryan Baxter investigating distributed tracing with Spring Cloud Sleuth
• wanna start trouble? Then check out this …

On behalf of the team, I am pleased to announce the release of the first release candidate of Spring Cloud Data Flow for Kubernetes 1.1.

Spring Cloud Data Flow for Kubernetes provides support for orchestrating long-running (streaming) and short-lived (task/batch) data microservices on Kubernetes.

The most significant change for this release can be found in the Spring Cloud Deployer for Kubernetes project. Thanks to community contributions from Donovan Muller and Rémon (Ray) Sinnema, we have added support for defining volumes and volume mounts for deployed apps. We support the volume types that have a model supported by the Fabric8 Kubernetes client's kubernetes-model…

We are pleased to announce that Spring Cloud Task 1.1.0.RELEASE is now available via Github and the Pivotal download repository. Many thanks to all of those who contributed to this release.

Spring Cloud Task 1.1.0 offers the following features:

This is the generally available release (GA) for 1.1.0. This release addresses key enhancements to the project to allow for better coverage of operational concerns for tasks in a cloud environment. Features new to the 1.1.0 line include:

• Updated error handling - 1.0.x stored stack traces that were the result of task executions within the TaskExecution#exitMessage field, requiring that this field perform double duty. First it was available for orchestration of tasks (similar to StepExecution#exitStatus in Spring Batch) as well as the storage of stack traces for debugging. In the 1.1.0 release, error messages have been moved to a new field TaskExecution#errorMessage so that each field has it's own, dedicated use.

• Updated customization options for partitioned batch jobs - In the 1.0.x line for Spring Cloud Task, when launching workers as tasks, there was not a way to customize the command line arguments provided to them. This is an issue in environments like CloudFoundry where you can use command line args to customize configuration without the need to re-push your app. In the new 1.1.0 release, we provide the ability to customize command line arguments via the CommandLineArgsProvider which is similar in functionality to the EnvironmentVariablesProvider introduced in 1.0.2.

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