Unfortunately I'm not familiar with a single resource for this, which probably contributes to developers being unfamiliar. There is a lot of domain specific knowledge depending upon if you're working with graphics, distributed computing, memory allocators, operating system kernels, network device drivers, etc.
The universal knowledge is learning to run well designed experiments, and this comes from practice. It's like how you would debug code without a debugger. There are profiling tools in some contexts that help you run these experiments, but at the highest level simply calculating the number of bytes that move through components divided by the amount of time it took is very enlightening.
It's valuable to have some rough familiarity of the limits of computer architecture. You can also do this experimentally; for example, you could test disk performance by timing how long it takes to copy a file much larger than RAM. You could try copying from /dev/zero to /dev/null to get a lower bound on RAM bandwidth. You can use netcat to see network throughput.
Bandwidth is only part of the picture; in some cases latency is important (such as servicing many tiny requests). Rough latency numbers are in [0, 1], but can also be learned experimentally.
Many popular primitives actually dont perform that great per node. For example something like a single MySQL or Spark node might not move than ~10MB/s per node; significantly lower than network bandwidth. You can actually use S3 to move data faster if it has a sequential access pattern :)
The universal knowledge is learning to run well designed experiments, and this comes from practice. It's like how you would debug code without a debugger. There are profiling tools in some contexts that help you run these experiments, but at the highest level simply calculating the number of bytes that move through components divided by the amount of time it took is very enlightening.
It's valuable to have some rough familiarity of the limits of computer architecture. You can also do this experimentally; for example, you could test disk performance by timing how long it takes to copy a file much larger than RAM. You could try copying from /dev/zero to /dev/null to get a lower bound on RAM bandwidth. You can use netcat to see network throughput.
Bandwidth is only part of the picture; in some cases latency is important (such as servicing many tiny requests). Rough latency numbers are in [0, 1], but can also be learned experimentally.
Many popular primitives actually dont perform that great per node. For example something like a single MySQL or Spark node might not move than ~10MB/s per node; significantly lower than network bandwidth. You can actually use S3 to move data faster if it has a sequential access pattern :)
[0] http://static.googleusercontent.com/media/research.google.co...
[1] https://gist.github.com/jboner/2841832