For Quonfig I landed on:
- Data model wise they are identical. Flags and configs can both be targeted. They can both use segments. They can both do partial rollouts. They can both have the same range of values (bool/number/duration/json/json-w-schema/etc)
- Its fine to use Flags for your Experiments/AB Tests, but that's just the "allocation engine". The rest of experimentation is the exposure tracking and goal tracking. Those ought live in your product analytics stack, because they are really just events. But its helpful to have a single place (flags) for the experiment allocation because then you can re-use segments for things like hold out groups / and just general targeting.
- The only real difference is that Flags are intended to be ephemeral and configs are intended to be permanent. A good UI should show you how long a flag has been alive and help you clean it up (or convert it to a config) if it's been true for everyone for too long.
- The use cases are different enough that it's worth keeping them in two separate UI.