rbspy VS austin-tui

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.

There is a "live" flamegraph TUI that uses Austin for those interested in Python profiling https://github.com/P403n1x87/austin-tui. The data collected can be exported and then converted into pprof, and analysed further with flameshow etc...

- Scoop

Austin is also simple to compile from sources as it only depends on the standard C library, if you don't have access to the above-listed repositories.

This new release of Austin brings enhanced support for many Python binary distributions across all the supported platforms, as well as a bugfix for the line number reporting. If you rely on Austin 2, upgrading to the latest version is strongly recommended.

Let me also remind you of some of the other existing Python tools powered by Austin, which have also seen new releases in the past few days, and that are easily available from PyPI:

https://github.com/P403n1x87/austin-tui