[throwaway2016a]

Depends on if your workload is CPU or I/O bound. It's true that CPU and RAM and proportional in Lambda and raising or lowering the RAM also raises and lowers your CPU.

I'm not sure why but I found with pre-compiled languages like Go it's not as big an issue (as long as your app is I/O bound). With Node.js I've found that increasing the size of the Lambda helps even with I/O bound functions. I assumed it was because the JIT compiling of the JS takes CPU but it also seems slower on subsequent runs and Lambda sleeps the apps it doesn't stop them (until you hit the end of the 5 minute reuse window). I give my Node.js a min of 1 Gig of RAM whereas I've been able to get some of my Go functions down to 128MB with no performance hit.

Which yes, means the Node.js functions are about twice as expensive per MS before you even consider that the Go function runs for less time. But in both cases I've still found it cheaper than servers due to efficiency even though strictly speaking it costs more than a server per GB/Ghz.