The problem is ecosystem wide - the documentation starts at 8/10 and is written for observability nerds where easy things are hard, and hard things are slightly harder.
I understand the role that all the different parts of OTel plays in the ecosystem vs InfluxDB, but if you pay attention to that documentation page, it starts off with the easiest thing (here's how you manually send one metric), and then ramps up the capabilities and functionality from here. OTel docs slam you straight into "here's a complete observaility stack for logs, metrics, and traces for your whole k8s deployment".
However, since OTel is not a backend, there's no pluggable endpoint + API key you can just start sending to. Since you were comparing the relative difficulties of sending data to a backend, that's why I responded in kind.
I do agree that it's more complicated, there's no argument there. And the docs have a very long way to go to highlight easier ways to do things and ramp up in complexity. There's also a lot more to document since OTel is for a wider audience of people, many of whom have different priorities. A group not talked about much in this thread is ops folks who are more concerned with getting a base level of instrumentation across a fleet of services, normalizing that data centrally, pulling in from external sources, and making sure all the right keys for common fields are named the right way. OTel has robust tools for (and must document) these use cases as well. And since most of us who work on it do so in spare time, or a part-time capacity at work, it's difficult to cover it all.
I understand the role that all the different parts of OTel plays in the ecosystem vs InfluxDB, but if you pay attention to that documentation page, it starts off with the easiest thing (here's how you manually send one metric), and then ramps up the capabilities and functionality from here. OTel docs slam you straight into "here's a complete observaility stack for logs, metrics, and traces for your whole k8s deployment".