First, I'd like to clarify the differences between SCDF and Stream/Task apps in the data pipeline.
SCDF is a lightweight Spring Boot app that includes the DSL, REST-APIs, and the Dashboard. Simply put, it serves as the orchestrator to define and deploy stream and task/batch data pipelines made of stream and task applications respectively.
The actual business logic, its performance, and the underlying resource consumption are at the individual Stream/Task application level. SCDF doesn't interfere with the app's operation, nor it contributes to the resource load. Everything, in the end, is standalone Boot apps - standalone Java processes.
Now, to your exploratory steps.
Disable embedded Tomcat server. I tried this once and SCDF couldn't tell the deployment status of the stream.
SCDF is a REST server and it requires the application container (in this case Tomcat), you cannot disable it.
Group multiple Kafka "source" topics to a single sink app. This is allowed by Kafka but unclear if SCDF will permit subscribing to multiple topics.
Again, there is no relation between SCDF and the apps. SCDF orchestrates full-blown Stream/Task (aka: Boot apps) into coherent data pipeline. If you have to produce or consumer to/from multiple Kafka topics, it is done at application level. Checkout the multi-io sample for more details.
There's the facility to consume from multiple topics directly via named-destination, too. SCDF provides a DSL/UI capability to build fan-in and fan-out pipelines. Refer to docs for more details. This video could be useful, too.
Switch to using Kubernetes deployer.
SCDF's Local-server is generally recommended for development. Primarily because there's no resiliency baked into the Local-server implementation. For example, if the streaming apps crash for any reason, there's no mechanism to restart them automatically. This is exactly why we recommend either SCDF's Kubernetes or Cloud Foundry server implementations in production. The platform provides the resiliency and fault-tolerance by automatically restarting the apps under fault scenarios.
From resourcing standpoint, once again, it depends on each application. They are standalone microservice application doing a specific operation at runtime, and it is up to how much resources the business logic requires.
