Spring Cloud Data Flow 1.0 GA 发布了，包括以下更新：
- Spring Cloud Data Flow’s Apache YARN Server 1.0 GA
- Spring Cloud Data Flow’s Kubernetes Server 1.0 GA
- Spring Cloud Data Flow’s Cloud Foundry Server 1.0 M4
- A Stream DSL that describes a data pipeline as a directed graph of individual applications.
- DSL support for named destinations that lets you consume events from any ‘pipe’ in the stream definition. This is referred to as tapping a stream. You can also combine the output from multiple streams.
- A deployment manifest that lets you define the resource usage of individual applications (CPU, Disk, Memory) as well as application instance count and how to partition data. You can also pass arbitrary application properties when deploying.
- Support application packaging as either a Spring Boot uber-jar or Docker image.
- Support deploying data microservices built using Spring Cloud Stream for long lived Stream applications that process an unbounded amount of data and Spring Cloud task for applications that process a finite set of data and then terminate. In turn these build upon Spring Boot.
- A shell application with tab-completion to create, deploy and monitor streams and tasks.
- A HTML5 Dashboard that lets you create, deploy, and monitor deployed streams and tasks.
- Support for basic HTTP and OAuth 2.0 authentication.
- ‘NoSql’ real-time analytics using Field Value and Aggregate Counters with HTTP endpoints on the server to access counter values. Counter data is backed by Redis.
- Use Spring Initializr to simplify the creation of stream applications.
- Spring Cloud Stream applications support RabbitMQ and Kafka 0.8
- Task and Stream Application Starters that you can use to customize the many source, processor, sink and task applications that we have provided.
- Whitelisting of Spring Boot application properties gives the shell/UI information to show a preferred set of boot properties to display for code completion and application info.