For most every workload I can think of, as their load increases it's always one resource in particular that's the limiting factor. (RAM/CPU/Storage/etc). So it makes sense to me that AWS instances focus on optimizing one particular resource type.

Would be interesting to hear about types of workloads that break this pattern. (Or maybe it's a few different types of workloads/services that need to be tightly integrated on one machine?)

In my experience, harder to also balance I/O so you’re close to hitting three limits, but update-heavy transactional workloads can manage it for disk-based DBMS’s.

So this is a rediscovery, at least an example, of what could be called the bottleneck principle of system performance analysis and optimization! Sooo, just look for the bottleneck(s), work on those, and f'get about everything else until, say, everything is equally a bottleneck at which time have a well balanced, call it optimized, which can be appropriate, configuration!

At times, e.g., at IBM's Watson lab, there has been a lot of work on applying queueing theory, analysis, and simulation to analyzing and then optimizing such systems, but, more closely to fully true than one might guess, all that really mattered were the bottlenecks(s)!