Good logging mechanisms, a strong infrastructure and pretty scalable
What is our primary use case?
Mostly the use cases are related to building a data pipeline. There are multiple microservices that are working in the Spring Cloud Data Flow infrastructure, and we are building a data pipeline, mostly a step-by-step process processing data using Kafka. Most of the processor sync and sources are being developed based on the customers' business requirements or use cases. In the example of the bank we work with, we are actually building a document analysis pipeline. There are some defined sources where we get the documents. Later on, we extract some information united from the summary and we… more »
Pros and Cons
"There are a lot of options in Spring Cloud. It's flexible in terms of how we can use it. It's a full infrastructure."
"The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation."
What other advice do I have?
While the deployment is on-premises, the data center is not on-premises. It's in a different geographical location, however, it was the client's own data center. We deployed there, and we installed the CDF server, then the Skipper server, and everything else including all the microservices. We used the PCF Cloud Foundry platform and for the bank, we deployed in Kubernetes. Spring Cloud Data Flow server is pretty standard to implement. The year before it was a new project, however, now it is already implemented in many, many projects. I think developers should start using it if they are not…