Spring Cloud Data Flow 1.5 RC1 released
The Spring Cloud Data Flow team is pleased to announce the release of
1.5.0 RC1. Follow the Getting Started guides for Local Server, Cloud Foundry, and Kubernetes.
Here are the highlights:
Switch to Hikari connection pool and restructure code to use fewer connections.
Several bug fixes in underling deployer libraries.
Editing a created/deployed stream is now possible from the Stream Builder. The application and deployment properties can be edited and re-deployed. The App version can be switched, too.
A new paginator component is added to all the list page. Switching from a list of 20, 30, 50, or 100 items per page is possible. This further simplifies the bulk operation workflows.
Introduction of end-to-end testing via Selenium and SauceLabs.
New release – Celsius.SR2
Updated Rabbit source/sink to work on PCF
Updated python apps
The client and the cluster version compatibility have be improved due to Core Workload APIs going GA. For example, a StatefulSet deployment for a partitioned streaming-pipeline dynamically resolves the version compatibility – no more hardcoded StatefulSet endpoints.
Extending the annotation support added to the “pod” configurations, it is now also possible to add custom annotations to “jobs” deployment.
Deploying with custom liveness and readiness probe ports is now supported.
Review the 1.5.0.M1 release blog for new feature improvements already added to the 1.5 code base.
Stay in touch…
As always, we welcome feedback and contributions, so please reach out to us on Stackoverflow or GitHub or via Gitter.
Please try it out, share your feedback, and consider contributing to the project!