Scientists from different communities, especially large-scale experimental facilities, have unique data and compute requirements that cannot be easily realized in a general-purpose supercomputing environment without significant modifications to either domain requirements or supercomputing operational configurations. One of the crucial customizations required is the orchestration of on-demand and auto-scale workflows on a largely batch-driven supercomputing system. On-demand, auto-scale and resiliency are features that are typically associated with cloud technologies. In order to empower a wide variety of users, concepts such as X-as-a-Service have been introduced. Experimental facilities' workflows from PSI that will leverage Data and Compute as a Service in supercomputing ecosystem at CSCS will be shared. Three use cases were implemented to demonstrate the feasibility and benefits of applying a cloud-driven approach to supercomputing ecosystems.