Having control lets you see if things changed. Optimization is changing things.
This team seems to be focused on control. I assume optimization is left to the service teams.
I get that they're different, but the whole point is optimization here. They're not gathering performance metrics just to hang them up on a wall and marvel at the number of decimal points, right? They presumably invested all the effort into this infrastructure because they think this much precision has significant ROI on the optimization side.
To me it seemed clear that the paper is about detecting regressions, which is control under my definition above. I still think of that as distinct from optimization.
It often isn't to make things go faster for an individual user (often times the driving factor of latency is not computation, but inter-system rpc latency, etc.). The value is to bin-pack processing more requests into the same bucket of CPU.
That can have latency wins, but it may not in a lot of contexts.