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Cloud Native Dataflow Orchestration

The video below will provide an overview of the Spring Cloud Data Flow architecture–including how it evolved out of Spring XD. Additionally, a streaming application will be deployed on each of the supported runtimes in a live demo.

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Recorded at SpringOne2GX 2015.
Speakers: Mark Fisher & Patrick Peralta
Big Data Track
Slides: http://www.slideshare.net/SpringCentral/cloud-native-data-flow-orchestration

The Spring Cloud Stream and Spring Cloud Task projects provide a simple and powerful framework for creating cloud-native data microservices for stream and batch processing. Each microservice in these distributed systems consists of a stand-alone Spring Boot application.

While it is possible to define data pipelines across these microservice apps manually, Spring Cloud Data Flow is an integrated orchestration layer that provides a highly productive deployment and management experience for development and ops. Streams and tasks are defined using the same DSL and shell/UI introduced with Spring XD. Furthermore, a pluggable runtime SPI allows Spring Cloud Data Flow to coordinate these applications across a variety of distributed runtime platforms including Apache YARN, Lattice, and Cloud Foundry.

This session will provide an overview of the Spring Cloud Data Flow architecture–including how it evolved out of Spring XD. Additionally, a streaming application will be deployed on each of the supported runtimes in a live demo.

Learn how moving from a traditional, on-premises delivery model to a cloud-based, software-as-a-service (SaaS) strategy is a high-stakes, bet-the-company game for independent software vendors. Brought to you in partnership with NuoDB.

Topics:
java ,spring ,cloud ,spring cloud

Published at DZone with permission of Pieter Humphrey, DZone MVB. See the original article here.

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