I'm trying to offer the perspective of someone who works with products that don't exist entirely on a server. If your product is a web service, the following might not apply to you.
IME creating diagnostic systems for various IoT and industrial devices, the "natural" stuff is relatively easy to implement (battery level, RSSI, connection state, etc) but it's rarely informative. In other words, it doesn't meaningfully correlate with the health of the system unless failure is already imminent.
It's the obscure stuff that tends to be informative (routing table state, delivery ratio, etc). But, complex metrics demand a greater engineering lift in their development and testing. There's also a non-trivial amount of effort involved in developing tools to interpret the resulting data.
Even if natural and informative were tightly correlated, which they aren't, an informative metric isn't necessarily actionable. You have to be able to use the data to improve your product. I can't charge the battery in a customer's device for them. I also can't move their phone closer to a cell tower. If you can't act on a metric, you're just wasting your time.