Once you have feature flags, an A/B test is a small step further: a flag with more than one variant, plus honest measurement. Here is how we do it at the edge, and the two bugs that quietly invalidate experiments.
I build this for Zenovay (web analytics). This assumes you already read flag config at the edge with no extra latency.
A flag is on/off. An experiment is a bucket.
The only new pieces are: assigning each user to a variant consistently, and logging exposure so you can measure.
Deterministic assignment (bug #1 if you get it wrong)
