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Managing Secrets with Vault

Passwords, API keys and confidential data fall into the category of secrets. Storing secrets the secure way is a challenge with limiting access and a true secure storage. Let’s take a look at Hashicorp Vault and how you can use it to store and access secrets.

How do you store Secrets?

Passwords, API keys, secure Tokens, and confidential data fall into the category of secrets.
That’s data which shouldn’t lie around. It mustn’t be available in plaintext in easy to guess locations. In fact, it must not be stored in plaintext in any location.

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Spring Cloud Data Flow 1.0 RC1 released

On behalf of the team I am pleased to announce the release of Spring Cloud Data Flow 1.0 RC1.

Several exciting new features have been added in this release which carry over to the other Data Flow Server implementations that were also released today.

Follow the links above for details on features unique to each individual runtime platform. The highlights of the release are:

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Spring Cloud Data Flow for Cloud Foundry 1.0.0.M3 released

I am pleased to announce the 1.0.0.M3 release of Spring Cloud Data Flow for Cloud Foundry, a team effort that encompasses many new features under the hood:

This third milestone builds upon the recent RC1 release of Spring Cloud Data Flow and also adds Cloud Foundry specific refinements. Some highlights include:

  • Alignment with Cloud Foundry’s global environment properties such as ORG, API, and URL as opposed to previous naming variants

  • Adds security integration to authenticate against OAUTH backend server that’s compatible with Cloud Foundry

  • Publishes security configurations for easier overrides when connecting to OAUTH backend server that’s compatible with Cloud Foundry

  • Preliminary iterations on performance testing on Cloud Foundry with and without taps’s in real-time streaming pipeline

  • Builds upon feature-toggle support from Spring Cloud Data Flow’s core project to conditionally refine what features get included in each release

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Spring Cloud Data Flow for Apache YARN 1.0.0.RC1 released

On behalf of the Spring Cloud Data Flow team, I am pleased to announce the 1.0.0.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

  • Adds several improvements to launching of short-lived applications a.k.a tasks to Apache YARN
  • Builds upon Spring StateMachine 1.1.0.RELEASE that includes new features, stability, and API improvements
  • Adds support to configure command line args as a separate set of properties to be passed to an application when it’s deployed. This is an important requirement for running Spring Batch jobs
  • Several Ambari plugin improvements to simplify provisioning of Spring Cloud Data Flow’s YARN server
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Spring Cloud Data Flow for Apache Mesos 1.0.0.RC1 released

I am pleased to announce the 1.0.0.RC1 release candidate of Spring Cloud Data Flow for Mesos, a team effort that encompasses many new features under the hood.

This release candidate builds upon the recent 1.0.0.RC1 release of Spring Cloud Data Flow. Some highlights include:

  • Improves orchestration mechanics by inheriting latest improvements to spring-cloud-deployer contracts and the supported functionalities.
  • Builds upon feature-toggle support from Spring Cloud Data Flow’s core project to conditionally refine what features get included in each release
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Spring Cloud Data Flow for Kubernetes 1.0.0.RC1 released

I am pleased to announce the 1.0.0.RC1 release candidate of Spring Cloud Data Flow for Kubernetes, a team effort that encompasses many new features under the hood.

This release candidate builds upon the recent 1.0.0.RC1 release of Spring Cloud Data Flow and also adds Cloud Foundry specific refinements. Some highlights include:

  • Implements the TaskLauncher SPI to support launching of short-lived applications a.k.a tasks. They will be created as Kubernetes jobs and each task launch will create a new pod as part of the Kubernetes job
  • Adds support to configure command line args as a separate set of properties to be passed to an application when it’s deployed. This is an important requirement for running Spring Batch jobs orchestrated as tasks using Spring Cloud Task programming model
  • Adds support for RDBMS “datasource” to supplement persistent repository requirements
  • Adds /info API to query health checks and to supplement probing requirements
  • Health endpoint improvements to standardize probing over readiness of all the applications orchestrated in Kubernetes
  • Adds docker image for Spring Cloud Data Flow’s Kubernetes server so it can be deployed as a Kubernetes replication controller and service
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This Week in Spring - June 21, 2016

Welcome to another installment of This Week in Spring! This week I’m in Amsterdam, Holland to speak at the local Spring User Groups and with local companies, and then it’s off to Krakow, Poland, Los Angeles, USA, Berlin, Germany and finally Seoul, South Korea! If you’re in any of those regions, hit me up. Anyway, there’s a lot of good stuff to get into this week so let’s get to it!

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Spring Cloud Task 1.0.0.RC1 is now available

We are pleased to announce the release of Spring Cloud Task 1.0.0.RC1. This is the first release candidate of the Spring Cloud Task project!

What’s New?

This release really represents the polishing of the functionality that existed within 1.0.0.M2:

  • The TaskRepository
  • Task listeners
  • Task integration with Spring Batch
  • Task integration with Spring Cloud Stream

There are a few minor breaking changes (renaming of a few methods) but those are all to get things right for our 1.0.0.GA. This release will serve as the baseline version of Spring Cloud Data Flow’s 1.0.0.RC1 as well.

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Spring Data release train Hopper SR2 released

On behalf of the Spring Data team I’d like to announce the availability of the second service release of the Spring Data Hopper release train. The release ships 103 issues fixed. We fixed a couple of bugs in the area of repository projections, especially for JPA users and introduce Hibernate 5.2 compatibility with this release (also already back-ported to the Gosling release train for inclusion in the upcoming service release). Hopper SR2 is a recommended upgrade for all Hopper users and also users of previous release trains.

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Spring Cloud Brixton.SR1 is available

On behalf of the team, I am pleased to announce that Service Release 1 of the Spring Cloud Brixton Release Train is available today. The release can be found in our Spring Release repository and Maven Central.

This is primarily a bug fix release with a few small features. Of particular note is a change that allows Brixton Eureka Servers to work with Angel Eureka clients.

The following modules were updated as part of Brixton.SR1:

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