CPU Utilization is Wrong (2017)

Summary

The metric we all use for CPU utilization is deeply misleading, and getting worse every year. What is CPU utilization? How busy your processors are? No, that's not what it measures. Yes, I'm talking about the "%CPU" metric used everywhere, by everyone. In every performance monitoring product. In top(1). What you may think 90% CPU utilization means: What it might really mean: Stalled means the processor was not making forward progress with instructions, and usually happens because it is waiting on memory I/O. The ratio I drew above (between busy and stalled) is what I typically see in production. Chances are, you're mostly stalled, but don't know it. What does this mean for you? Understanding how much your CPUs are stalled can direct performance tuning efforts between reducing code or reducing memory I/O. Anyone looking at CPU performance, especially on clouds that auto scale based on CPU, would benefit from knowing the stalled component of their %CPU. What really is CPU Utilization? The metric we call CPU utilization is really "non-idle time": the time the CPU was not running the idle thread. Your operating system kernel (whatever it is) usually tracks this during context switch. If a non-idle thread begins running, then stops 100 milliseconds later, the kernel considers that CPU utilized that entire time. This metric is as old as time sharing systems. The Apollo Lunar Module guidance computer (a pioneering time sharing system) called its idle thread the "DUMMY JOB", and engineers tracked cycles running it vs real tasks as a important computer utilization metric. (I wrote about this before.) So what's wrong with this? Nowadays, CPUs have become much faster than main memory, and waiting on memory dominates what is still called "CPU utilization". When you see high %CPU in top(1), you might think of the processor as being the bottleneck – the CPU package under the heat sink and fan – when it's really those banks of DRAM. This has been getting worse. For a long time pro...