You've got some data from some A/B tests you ran. Presumably, you want to evaluate the differences between the results coming in from A and B. I think I'd do this as a dashboard with separate visualizations for "A" and "B". e.g. an A gauge and a B gauge for data that fits the gauge visualization, and an A table and a B table for tabular data, etc. Then, I'd place those side-by-side to get some idea of how the two tests compare.
Does that make sense?
I find that things get hairy when you have too many interconnected, nested aggs, etc in Kibana visualizations, so I'd try to think of a simpler compromise.
This would be too hard for the eyes to compare. The main thing in AB is that each pair may have very different patterns compared to other pairs and there can be dozens of pairs.
Getting each pair's diff on the same graph would be key, so that you can quickly tell which one deviates either on the positive or negative side. I would save the operator hours at a time, since we have a lot of metrics.
Again doing the group by "pair name" instead of server, would not let me do the derivative and calculation (multiply by -1) per server.