Spring Cloud Data Flow is used for asynchronous workloads. We are working on streams. For example, a workload is generated at a particular point, and at the source, it gets passed down through a series of processors down to a sink and within that sink, it is persisted in a database.
It reduced the overhead of microservices communication.
The most valuable features of Spring Cloud Data Flow are the simple programming model, integration, dependency Injection, and ability to do any injection. Additionally, auto-configuration is another important feature because we don't have to configure the database and or set up the boilerplate in the database in every project. The composability is good, we can create small workloads and compose them in any way we like.
Spring Cloud Data Flow could improve the user interface. We can drag and drop in the application for the configuration and settings, and deploy it right from the UI, without having to run a CI/CD pipeline. However, that does not work with Kubernetes, it only works when we are working with jars as the Spring Cloud Data Flow applications.
When we are using Docker images as the applications, the UI does not work, or it is not clear how it works.
In a feature release, it would be beneficial if there could be more supported languages. They only support Spring, Node.js, and Python.
I have been using Spring Cloud Data Flow for approximately one month.
The stability of Spring Cloud Data Flow is very good. We have not had any issues. The only issue we have is with our own understanding.
Spring Cloud Data Flow is infinitely scalable horizontally. It scales well.
We have two people using this solution and we will increase usage over time.
I have not used the support from Spring Cloud Data Flow. There is a lot of documentation available, but it could be improved.
I have only worked with in-house-built solutions for asynchronous workloads. Spring Cloud Data Flow is the first solution that is not in-house I have used.
The initial setup of Spring Cloud Data Flow was complex. I deployed it on Kubernetes, and it is complex. For example, setting up Kafka and ZooKeeper. I spent more than one week setting it up.
When you're deploying this application on Kubernetes, there is only one resource that I could find, and it was very opinionated and unorganized. It's not extensive documentation, it's only a tutorial.
I rate the setup of Spring Cloud Data Flow a two out of five.
I did the full deployment of the solution.
If you want support from Spring Cloud Data Flow there is a fee. The Spring Framework is open-source and this is a free solution.
The solution requires little maintenance.
My advice to others is for them to follow the documentation. The solution is very well-designed and they deliver on their promises.
I rate Spring Cloud Data Flow a seven out of ten.
