Spring Team
Janne Valkealahti

Janne Valkealahti

Spring Data Hadoop Engineer

London, UK

Janne is a member of Spring Data team focusing on "Spring for Apache Hadoop", "Spring YARN" , "Spring Statemachine" and "Spring XD". After spending 10 years handling IT systems in a Finnish bank he joined SpringSource and has called London his home for past few years.
Blog Posts by Janne Valkealahti

Spring Statemachine 1.2.0 Released

We’re pleased to announce a release of Spring Statemachine 1.2.0.RELEASE. Artifacts are available either from Maven Central or from Spring Repository.

Let’s see what we did for this initial 1.2.x release

  • Usual bug fixes and small enhancements.
  • Support for UML submachines.
  • New Spring Data Repository abstraction keeping machine configurations in an external repository with built-in support for Redis, MongoDB and JPA.
  • New samples.
  • New support for state do actions.
  • New monitoring and tracing API’s.
  • Initial support for Spring Boot auto-config.
  • New transition and state error action concepts.
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Spring Statemachine 1.2.0.RC1 Released

We’re pleased to announce a release candicate of Spring Statemachine 1.2.0.RC1. Artifacts are available from Spring Repository.

What we got into this release:

  • Usual bug fixes and small enhancements
  • New api’s for tracing and monitoring
  • New monitoring sample
  • Full repository config support for Redis, MongoDB and JPA
  • Boot auto-config enhacements
  • Lot of documentation enhacements

Full changes as usual are available from changelog. We’re planning to fire up 1.2.0.RELEASE before xmas and possibly do a second release candicate if any major issues are found.

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Spring Cloud Data Flow for Apache YARN 1.1.0.RC1 released

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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Spring Statemachine 1.2.0.M1 Released

We’re pleased to announce a first milestone release of Spring Statemachine 1.2.0.M1. Artifacts are available from Spring Repository.

What we got into this first milestone:

  • Usual bug fixes and small enhancements
  • Support for UML submachines
  • New Repository abstraction keeping machine configuration in an external repository
  • New support for state actions.
  • New transition error action concepts

There has been a support for complex state hierarchy from a day one but trouble was that everything had to be defined in a same state configuration. New submachine support adds a feature where a state can be associated with other machine which allows some level of re-use and makes configuration more clean.

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Spring Cloud Data Flow for Apache YARN 1.0.2 released

We are pleased to announce the release of Spring Cloud Data Flow for Apache YARN 1.0.2.RELEASE.

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

Apart from usual minor fixes, we have worked on the following themes.

  • Builds upon Spring Cloud Data Flow’s 1.0.1.RELEASE
  • Support for Apache Ambari 2.4
  • Adds Apache Ambari installation of Spring Cloud Data Flow for HDP 2.5 stack
  • UX improvements around Apache Ambari configuration settings and quicklinks
  • Adds support to interact with kerberized Apache Kafka cluster
  • Yarn deployer APIs and the auto-configuration improvements
  • Certification of partitioned batch-jobs running as short-lived Tasks in YARN
  • Improved documentation
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Spring Cloud Data Flow for Apache YARN 1.0.1 released

We are pleased to announce the release of Spring Cloud Data Flow for Apache YARN 1.0.1.RELEASE.

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

Apart from usual minor fixes, we have worked on the following themes.

  • Support for kerberos and integration to automated ambari kerberos setup.
  • Support for HDFS HA Namenode setup.
  • New extension to dataflow-shell adding hadoop fs basic commands.

For a complete list of changes and improvements, please refer to
1.0.1.RELEASE server release, 1.0.1.RELEASE deployer release, 1.0-2.RELEASE rpm release and 1.0-2.RELEASE ambari plugin release.

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Spring Cloud Data Flow for Apache YARN 1.0.0 released

We are pleased to announce the release of Spring Cloud Data Flow for Apache YARN 1.0.0.RELEASE.

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

This project was originally conceptualized with the goal to supplement the existing Spring XD users who have investments running streaming and batch data pipelines in a more traditional bare-metal setup. We wanted to provide migration path to help port over their existing investments and the tools and techniques to reap the benefits of microservices style architecture.

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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 Statemachine 1.1.0 Released

We’re pleased to announce a release of Spring Statemachine 1.1.0. I’d like to start by saying thank you for all who contributed in any way to make this happen. Artifacts are available either from Maven Central or from Spring Repository.

What we got into this release(compared to 1.0.x):

  • Comprehensive support for Spring Security.
  • Context integration with [email protected] has been greatly enhanced.
  • StateContext is now a first class citizen with how user can interact with a State Machine.
  • Features around persistence has been enhanced with a build-in support for redis.
  • New feature helping with persist operations.
  • Configuration model classes are now a public API.
  • New features in timer based events.
  • New Junction pseudostate.
  • New Exit Point and Entry Point pseudostates.
  • Configuration model verifier.
  • New samples.
  • UI modeling support using Eclipse Papyrus.
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Spring Cloud Data Flow for Apache YARN 1.0.0.M2 released

On behalf of the Spring Cloud Data Flow team, I am pleased to announce the 1.0.0.M2 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, UI and Flo) 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 second milestone

  • builds upon the 1.0.0.M1 release of Spring Cloud YARN Deployer.
  • builds upon the 1.0.0.M3 release of Spring Cloud Data Flow.
  • Adds Spring Cloud Task support to orchestrate short-lived tasks including Spring Batch jobs in a YARN cluster.
  • Improved IP address discovery for internal coordination.
  • Adds support to host, resolve and register OOTB apps from HDFS.
  • Adds installable RPM bits.
  • Adds Ambari plugin to provision SCDF on YARN.
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