I strongly disagree. At large scale, there are huge advantages to running multiple mysqld on one physical host. Facebook does this across their entire DB fleet! Most of their DB hosts run 2 mysqld but some run 8 or more -- it depends on which workload the host is part of.
The original motivation was to support multiple hardware generations. PCIe flash cards have become much larger over the years very quickly -- much faster than older cards become end-of-life. The result is that if you're running a large fleet of database hosts for many years, their storage capacity will differ greatly, both between datacenters (e.g. older DCs will have older hardware on average) and eventually within a datacenter that gets a partial refresh.
By defining automation configuration that is smart enough to know that some hosts get 1 mysqld and others get 2 mysqld, based on storage / hw generation, there's a much better flash utilization win.
This setup also enables faster replacement of failed hosts. Say each host has N mysqld, all part of different pools. If a host fails then you need to hot-copy the data set of each of these, from other replicas in each affected pool, to a new location. The trick is the replacements can copy from N different source hosts, and even go to N different destination hosts as well. This permits massively faster hot copying behavior vs having a single giant mysqld per host.
tl;dr it requires a lot of automation but there are very valid reasons for doing this.
That said, I would not advocate using Docker to achieve this. It provides little benefit for this scenario. If you're good at calculating mysqld memory usage, you can already just set the buffer pool and per-session buffers to a size that prevents multiple mysqlds from ever swapping. Meanwhile cpu and network rarely are points of saturation for a db host so that tends to work out fine without a quota system.
So that leaves i/o as the main resource that the processes will compete for. But Docker cannot provide i/o isolation.
From what I understand, Google/YouTube containerizes their data stores, but their systems around containerization are far more advanced than anyone else's. So I assume they've already solved this problem internally, but that doesn't mean the current state of the art in the open source world is up to the task yet.