rbspy VS flamegraph

We used rbspy to generate the flamegraph:

You could use rbspy to profile the EventMachine process as it's doing the workload, and try to see there where most of the time is being spent.

Not sure what your issue is and you got some of this info from strace, but FYI rbspy can also help profile where a running Ruby process is spending its time: https://rbspy.github.io/. I think it's a little more helpful than strace in that it should bring it back to Ruby code rather than just showing the raw syscalls.

Even the most general profiler tool will show you each statement's accumulated time. These are called statistical profilers and give you a panoramic view of what the test is doing. An example of such a profiler is rbspy:

As a result, you need to craft a specific routine for each interpreter runtime (in some cases, each version of that runtime) to obtain symbol information. Educated eyes might have already noticed, it's not an easy undertaking considering the sheer amount of interpreted languages out there. For example, a very well known Ruby profiler, rbspy, generates code for reading internal structs of the Ruby runtime for each version.

For production, it depends on what the process is built with. There are possibly better tracing tools than just strace. For example Java has JMX, Go has pprof. There's also things like rbspy for Ruby.

I was a bit surprised to find out that the tool used to generate the flamegraph for Ruby (rbspy [1]) is written in Rust. lol

[1] https://github.com/rbspy/rbspy

Maybe https://github.com/rbspy/rbspy would allow you to profile the running ruby process handling web sockets?

c function is not very helpful to find the performance problem, so we dug deeper.

You can install cargo-flamegraph with cargo install flamegraph. There are some underlying requirements to be able to use cargo-flamegraph; you will want to take a look at the repo here to make sure you have the right dependencies.

I tried to diagnose the issue with flamegraph, but unfortunately the flamegraph didn't show anything beyond the next call for some reason

having some tools to identify slowness origins (flamegraph is one... but not sure it's the way to go)

I'm currently implementing a solution for the first part of the day 16. It work but it is really slow... I'd like to : - understand why - having some tools to identify slowness origins (flamegraph is one... but not sure it's the way to go) - eventually have some clue/solution/idea - have general feedback on what in my "coding style" is not appropriate for rust (I come from java/kotlin/ts even if I've already coded a bit in c/c++) : for example I love iterator & sequence but i feel they are not really suited to overuse in rust (mostly because of async & result).

Use a profiler. Flamegraph is a good way to visualise profiler output. This lets you identify which functions are taking up a large amount of time - and hence helps you identify where to focus your optimisation efforts.

You tried trying to see what takes the most time under load via flames? https://github.com/flamegraph-rs/flamegraph

Well, in cases like that the answer is straight forward, use a profiler like https://github.com/flamegraph-rs/flamegraph

I don't see any obvious problems with your algorithm. I've had luck using cargo-flamegraph to identify the slow parts of my code. That's going to show you which parts to focus on improving the performance of!

From the readme of cargo flamegraph: