Correct! Many folks have more complicated deployments in the cloud, and we're trying to align (as close as humanly possible) your on-prem stack with your cloud

Correct! Many folks have more complicated deployments in the cloud, and we're trying to align (as close as humanly possible) your on-prem stack with your cloud stack, to minimize the pain in migration. If you have a single container, and a simple pipeline, this may be a bit more than you need. We've just found that there are normally 5 or more services/systems that people wire together to create an ML stack, and that's what we're trying to solve for/simplify. Disclosure: I work at Google on Kubeflow