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.
For detailed list of deployer improvements review the changes listed in the Spring Cloud Deployer for Kubernetes 1.1.0.RC1 marker.
We have also updated the provided scripts for testing the server on Google Cloud Container Engine. We now use Kafka 0.10.1 in order to support the latest 1.1 version of the app starters.
The 1.1.0.RC1 release builds on the recent 1.1 RC1 release of the core Spring Cloud Data Flow project.
Review the Spring Cloud Data Flow for Kubernetes 1.1.0.RC1 marker to learn more about the incremental improvements.
Docker images containing the Spring Cloud Data Flow Server for Kubernetes for all releases are available from the Docker Hub repo.
To get started using Spring Cloud Data Flow for Kubernetes follow the steps outlined in the reference documentation.