Off the top of my head, maybe a maintained "ml-engine aligned" kubeflow setup, to the extent that's possible. The use case I'm think of is an ml dev team build

Off the top of my head, maybe a maintained "ml-engine aligned" kubeflow setup, to the extent that's possible. The use case I'm think of is an ml dev team building on kubeflow and proving a system. Then wanting to transfer it to a non-engineering team, yet wash their hands of any ongoing infrastructure ops responsibility. Knowing that a "ml-engine aligned" kubeflow config would transfer cleanly (including associated bells and whistles) would make that a much more attractive option. Caveat: I'll admit I'm not keeping up on what's in the managed offering, but I'm assuming there are a number of value-adds of the type that end users like (visualizations, etc).