An baseline implementation for SKA FaaS / Serverless approach

Having implemented clusters with Kubernetes, container orchestration and a federation of services at Kubernetes level with KubeFed/Karmada, we thought that the next logical step would be to provide a platform for FaaS, such as OpenFaaS or OpenWisk, on top of Kubernetes/KubeFed that allows to include a subset of functions (from radioastronomy pipelines, such as cleaning, flagging, . ...) that can be used from a python package (or from any other language, for example ska-science-tools) and used in a JupyterNotebook, from source code or from another service (code agnostic). These functions, as they run inside Kubernetes (or KubFed) can be (virtually) infinitely scalable, provide HA, can be distributed or geolocated, run on slurm, and can have brokering capabilities. With it, we can provide users with scientific tools at scale.