Microservices are definitely offering best practice guidance for those architecting cloud-native applications. The ability to quickly create small services that can be individually deployed, configured and scaled, as building blocks for scalable, highly distributed and fault-tolerant systems has been causing every company to rethink on how to architect modern systems and making Spring Boot shine in popularity.
In the same perspective, in order to achieve the same level of resilience, scalability, and flexibility for stateful systems we need to start building our data components over the concepts of Data Microservices.
This session will introduce Spring Cloud Stream from a Data Microservices perspective. We’ll explore its architecture model, highlighting the scalability, high availability, importance of dynamic transport biding layer and different options for orchestration/cloud deployment. We’ll then give an architecture walk-through on how Spring Cloud Data Flow orchestrates those Data Microservices into an advanced data pipelining solution, exemplified by a live demo.
Recorded at SpringOne Platform 2016.
Speaker: Fred Melo
{{ parent.title || parent.header.title}}
{{ parent.tldr }}
{{ parent.linkDescription }}
{{ parent.urlSource.name }}