Clearly you've never deployed a 30 GB image, where 26 GB is the final, application building layer. And that's with staged building and working to minimize the size of overlay layers, redundancy, etc. Okay, so that might be a particularly pathological case, but still, resources are resources. I'm fine with a multi-gig machine learning image where the model and most of the heavy stuff is in a middle layer and the only redeploy is a few MB of python code. But that architecture isn't always easy, either.