Cloud Native Spring: Streams and Tasks

In this session, we'll see how to develop microservices that are components of a flow of data, but that do not necessarily involve REST. We'll also see how to develop ephemeral microservices–microservice that are triggered to perform a job, then shutdown when that job is complete. Specifically, we'll look at Spring Cloud Stream for flow-based microservices, Spring Cloud Task for ephemeral microservices, and Spring Cloud Data Flow which orchestrates those stream- and task-based services.

Microservice-architecture presents many benefits, not the least of which include opportunities to develop, evolve, scale, test, and deploy individual modules of an application independently from the rest of the application. But once an application is broken apart, a new set of challenges arises.

Microservices are commonly thought of as small REST-based services that are assembled to form a larger, more complete application. In reality, however, REST is only the communication mechanism which is only a implementation detail and not intrinsic to the notion of microservices. Meanwhile, data processing and integration between various components of an application and external services is a key factor of many applications. In cloud native applications, this kind of data flow and processing is still relevant.

About Craig Walls

Craig Walls is a Principal Engineer, Java Champion, Alexa Champion, and the author of Spring AI in Action, Spring in Action, and Build Talking Apps. He's a zealous promoter of the Spring Framework, speaking frequently at local user groups and conferences and writing about Spring. When he's not slinging code, Craig is planning his next trip to Disney World or Disneyland and spending as much time as he can with his wife, two daughters, 1 bird and 2 dogs.

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