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Spring Cloud Data Flow 1.0.0 M3 Released

Releases | Mark Fisher | April 29, 2016 | ...

On behalf of the team, I am pleased to announce the 1.0.0.M3 release of Spring Cloud Data Flow.

Over the last few months, we have added exciting new features and improvements to the overall orchestration of data microservices on a variety of platforms. We have also made some changes that significantly benefit developers, such as exposing Spring Boot Starters for all of the stream and task applications we publish. Following are some of the highlights from this release:

  • Provides the foundation for the following Data Flow Server implementations that have also been released today:
  • Introduces and builds upon the Spring Cloud Deployer Service Provider Interface
    • New multi-platform application deployment model factored out of Spring Cloud Data Flow itself for general purpose use, including AppDeployer and TaskLauncher to deploy long-running and short-lived microservices, respectively.
    • Improved application resolution strategy with support for maintaining a registry of applications as http, file, maven, docker, or hdfs artifacts
  • Builds upon Spring Cloud Stream 1.0.0.RC3
  • Builds upon Spring Cloud Task 1.0.0.M2
  • Improves DSL support for streaming and batch pipelines
  • Adds "tap" support for streaming and batch pipelines
  • Applications
    • Supports out-of-the-box stream applications built from the new Stream Application Starters project (auto-generated apps for both Kafka and RabbitMQ binders)
    • Supports out-of-the-box task applications built from the new Task Application Starters project
    • Adds several new out-of-the-box stream and task applications
    • Improves custom application registration mechanics from the Shell and Dashboard
  • Dashboard
    • New and improved Dashboard
    • Adds Batch and Task support
    • Adds "Apps" tab to monitor and manage out-of-the-box and custom applications
  • Flo for Spring Cloud Data Flow
    • Modern look and feel with several UX improvements around the palette, auto-layouts, auto-linking, canvas, nodes, node connectors, and many more
    • Adds support for a scriptable-transform processor that accepts ruby, groovy, python, or javascript code for runtime compute logic
    • Adds visual distinction between primary and tap’d pipelines
    • Adapts to Angular style tooltips
    • Graph layout optimizations

  • Improved IT and TCK tests

  • Adds new samples
  • Adds new logo

For the complete list of features, bug-fixes, and improvements, please refer to the closed 1.0.0.M3 GitHub issues.

We welcome feedback and contributions! If you have any questions, comments or suggestions, please let us know via GitHub Issues, StackOverflow, or using the #SpringCloudDataFlow hashtag on Twitter.

We have aggressive plans for the upcoming RC release. Stay tuned!

Last but not least... check out this brand new website to learn how Spring Accelerates Cloud Native Java Application Development!

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