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Webinar Replay: Stream Processing in the Cloud with Data Microservices

Speakers: Marius Bogoevici, Pivotal

The future of scalable data processing is event-driven microservices! They provide a powerful paradigm that solves issues typically associated with distributed applications such as availability, data consistency, or communication complexity, and allows the creation of sophisticated and extensible data processing pipelines.

Building on the ease of development and deployment provided by Spring Boot and the cloud native capabilities of Spring Cloud, the Spring Cloud Stream project provides a simple and powerful framework for creating event-driven microservices. They make it easy to develop data-processing Spring Boot applications that build upon the capabilities of Spring Integration. At a higher level of abstraction, Spring Cloud Data Flow is an integrated orchestration layer that provides a highly productive experience for deploying and managing sophisticated data pipelines consisting of standalone microservices. Streams are defined using a DSL abstraction and can be managed via shell and a web UI. Furthermore, a pluggable runtime SPI allows Spring Cloud Data Flow to coordinate these applications across a variety of distributed runtime platforms such as Apache YARN, Cloud Foundry, Kubernetes, or Apache Mesos.

You’ll see live deployment demos on different platforms ranging from local cluster to a remote Cloud to show the simplicity of the developer experience.

Spring Cloud Data Flow 3 part webinar series:
Spring Cloud Task
Spring Cloud Data Flow

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