That's not a fair assessment and I'm surprised this is the top comment. In this case, the huge advantage to a containerized setup is that everything is now easily portable. If his server goes down, or he just decides to move, OP can now deploy all of his websites onto another server instantly. He also quotes the ability to build (and test) locally before shipping images to production, which is a really neat workflow. Improved security comes as an added bonus.
As for the "s3 costs of docker image", it's a few cents per month.
I don't think the problem of "renormalizing" signed distance fields can be cracked, at least not in a generic way that's fast enough for realtime rendering. I would agree this strongly limits the possibilities for making simple modeling tools based on SDFs, because whenever you use interesting transformations, you also need to be hacking away at the correctness of the field. Because of this, it's hard to make simplified tools for modeling and rendering interesting things using SDFs: you can't abstract away the fact that you're effectively writing a distance estimator function, and you'll always want to be able to dig down to the lowest programming level in order to make things work. This is a problem for popularization, but it doesn't prevent the technique from being useful in some domains and applications.
Some extinct dog breeds are pretty wonky. The Turnspit dog was specifically bred to nicely fit into a kind of hamster cage, so that the dog would power a turning spit for roasting meats. Of course, the dog becoming obsolete led to its extinction.
As for the "s3 costs of docker image", it's a few cents per month.