3. Introducing Spring Cloud Data Flow

3. Introducing Spring Cloud Data Flow
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Spring Cloud Data Flow is a cloud-native orchestration service for composable microservice applications on modern runtimes. With Spring Cloud Data Flow, developers can create and orchestrate data pipelines for common use cases such as data ingest, real-time analytics, and data import/export.

Spring Cloud Data Flow is the cloud native redesign of Spring XD – a project that aimed to simplify development of Big Data applications. The stream and batch modules from Spring XD are refactored as Spring Boot based stream and task/batch microservice applications respectively. These applications are now autonomous deployment units and they can "natively" run in modern runtimes such as Cloud Foundry, Apache YARN, Apache Mesos, and Kubernetes.

Spring Cloud Data Flow offers a collection of patterns and best practices for microservices-based distributed streaming and task/batch data pipelines.

3.1 Features

Develop using DSL, REST-APIs, Dashboard, and the drag-and-drop GUI - Flo
Create, unit-test, troubleshoot and manage microservice applications in isolation
Build data pipelines rapidly using the out-of-the-box stream and task/batch applications
Consume microservice applications as maven or docker artifacts
Scale data pipelines without interrupting data flows
Orchestrate data-centric applications on a variety of modern runtime platforms including Cloud Foundry, Apache YARN, Apache Mesos, and Kubernetes
Take advantage of metrics, health checks, and the remote management of each microservice application