Spring Team
Thomas Risberg

Thomas Risberg

Software Engineer focusing on Big Data

New Hampshire, USA

My current focus is on the "Spring Cloud Data Flow", "Spring for Apache Hadoop" and "Spring Data JDBC Extensions" projects. I'm a co-author of "Spring Data, Modern Data Access for Enterprise Java" published by O'Reilly Media in 2013 and "Professional Java Development with the Spring Framework" published by Wiley in 2005.
Blog Posts by Thomas Risberg

Spring for Apache Hadoop 2.5.0.RC1 released

New release candidate for Spring for Apache Hadoop 2.5

We are pleased to announce the Spring for Apache Hadoop 2.5 release candidate release.

We continue to provide version specific artifacts with their respective transitive dependencies in the Spring IO milestone repository:

The 2.5 version is primarily a bug fix and version upgrade release.

See the release changelog for details.

We continue to provide version specific artifacts with their respective transitive dependencies in the Spring IO milestone repository:

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Spring Cloud Data Flow 1.2 M3 released

On behalf of the team, I am excited to announce the release of the third 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.

Highlights of the 1.2 M3 release:

Companion Metadata Artifact

As part of the long awaited feature to improve access to app properties info for both shell and Dashboard, we are introducing a new optional artifact for both Stream and Task applications - we are calling it the “companion metadata artifact”. Through this functionality, the streaming and task applications and their properties are first-class citizens for both Docker and Maven based application artifacts.

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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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Spring Cloud Data Flow for Kubernetes 1.1 RC1 released

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.

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Spring Cloud Data Flow for Kubernetes 1.1 M2 released

On behalf of the team, I am pleased to announce the release of the second milestone 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.

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.

The most significant changes for this release can be found in the Spring Cloud Deployer for Kubernetes project. Thanks to several community contributions, we have significantly improved the customization options available for launching Kubernetes apps. We now support resource requests in addition to resource limits and the imagePullPolicy can now be specified. You can also specify the startup command and the entryPoint type used for the Docker image as well as override exposed ports and specify environment variables when deploying apps. For detailed list of deployer improvements review the changes listed in the Spring Cloud Deployer for Kubernetes 1.1.0.M1 marker.

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Spring Cloud Data Flow for Kubernetes 1.1 M1 and 1.0.1 GA released

On behalf of the team, I am pleased to announce the release of the first milestone of Spring Cloud Data Flow for Kubernetes 1.1 along with a 1.0.1 maintenance release.

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

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.

Read more...

Spring Cloud Data Flow for Apache Mesos 1.0 GA released

On behalf of the team, I am excited to announce the General Availability of Spring Cloud Data Flow for Apache Mesos 1.0.

Spring Cloud Data Flow for Apache Mesos provides support for orchestrating long-running (streaming) and short-lived (task/batch) data microservices on Apache Mesos. We launch stream apps using Application Groups on Marathon and tasks as Chronos one-time jobs. The release includes a template JSON script for deploying the Spring Cloud Data Flow server on Marathon. We also include sample scripts for deploying Redis, MySQL and Rabbit MQ on Marathon to be used for testing a complete deployment. In addition to running on an Apache Mesos cluster, we also support running on a Mesosphere DC/OS cluster.

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Spring Cloud Data Flow 1.1 M1 and 1.0.1 GA released

On behalf of the team, I am excited to announce the release of the first milestone of Spring Cloud Data Flow 1.1 along with a 1.0.1 maintenance release for the 1.0 version.

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.

1.1 M1 release

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 1.1.0.M1 release:

Read more...

Spring Cloud Data Flow for Mesos 1.0 RC2 released

We are pleased to announce the 1.0.0.RC2 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 GA release of Spring Cloud Data Flow. Some highlights include:

  • We now run the Spring Cloud Data Flow Server as a Docker image on Marathon, a container orchestration platform for Mesos.
  • This release adds features to support stream partitioning and scaling
    • Currently partitioning and scaling of sinks and processors are handled by using multiple application deployments, one for each app instance, identified by an index appended to the name.

    • Scaling of sources is handled by using additional application instances.
  • Streams are now deployed using Marathon Application Groups so it is easier to identify the different apps making up a stream.
  • We have added support for launching tasks using Chronos, a fault tolerant job scheduler for Mesos.
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Spring Cloud Data Flow for Kubernetes 1.0 GA released

We are pleased to announce the release of Spring Cloud Data Flow’s Kubernetes 1.0.0.RELEASE.

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

This project was originally conceptualized by the community and we are thankful to Florian Rosenberg for his early contributions that eventually made it into the official Spring Cloud Deployer for Kubernetes project. Building upon this theme, we recently bumped into Donovan Muller’s blog, where he walks through his experience extending the Spring Cloud Deployer project for OpenShift, paving the path for Spring Cloud Data Flow to orchestrate data microservices on OpenShift.

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