I agree. If you actually know what you're doing you can use perf and/or ftrace to get highly detailed processor metrics over short periods of time, and you can see the effects of things like CPU stalls from cache misses, CPU stalls from memory accesses, scheduler effects, and many other things. But most of these metrics are not very actionable anyway (the vast majority of people are not going to know what to do with their IPC or cache hit or branch hit numbers).

What most people care about is some combination of latency and utilization. As a very rough rule of thumb, for many workloads you can get up to about 80% CPU utilization before you start seeing serious impacts on workload latency. Beyond that you can increase utilization but you start seeing your workload latency suffer from all of the effects you mentioned.

To know how much latency is impacted by utilization you need to measure your specific workload. Also, how much you care about latency depends on what you're doing. In many cases people care much more about throughput than latency, so if that's the top metric then optimize for that. If you care about application latency as well as throughput then you need to measure both of those and decide what tradeoffs are acceptable.