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Cloud Native Dataflow Orchestration

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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.

· Cloud Zone ·
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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.

Cloud Foundry saves app developers $100K and 10 weeks on average per development cycle. Download the 2018 User Survey for a snapshot of Cloud Foundry users’ deployments and productivity. Find out what people love about the industry standard cloud application platform.

Topics:
java ,spring ,cloud ,spring cloud

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