Motivation
This document serves as a place for brainstorming ideas for Model & Dataset CRD design. The general goal is to design reusable CRDs that can be shared by various higher level machine learning tasks and frameworks.
Goals
- What do the CRD controllers do? Define the exact responsibilities of model & dataset CRDs and controllers.
- How will the higher level tasks, i.e. federated learning, model serving etc, utilize the services provided by model & dataset CRDs.
- Cloud edge communication mechanism for the CRD controllers: do they share the existing port 10000, or use a new port exclusively for AI purpose? Related: how do cloud workers and edge workers communicate? Cloud workers can be scheduled in cloud worker nodes, which means they can be deployed as a K8s service and have an publicly routable endpoint. Can KubeEdge operate in hybrid mode, i.e. having both cloud worker nodes and edge nodes?
Use Cases
Model serving
Upon creating a model CRD object, model controller