If you want to chart on the same graph things with very different orders of magnitude size (and some things varying in size by orders of magnitude) then my first thought would be to choose a log scale for one axis. It doesn't look like this module supports that natively, but nothing stops you from taking logs of your values. (log($x)/log(10) would be traditional.) Now all values fit sensibly on one graph and you don't have to figure out how to split them.

Common examples of data which we normally scale this way are sound volume and earthquake intensity. Both are normally quoted as a log of intensity.

If you really want to take your original approach, I would take the largest dataset, and group it with things which are within a factor of 10 of its size. Then put everything else in group 2. But then you have to figure out how to handle the situation where a dataset keeps jumping from one chart to another, and you can't get a good graph of response time variations of more than a couple of orders of magnitude.

I'd suggest trying the log scale first.