Interesting approach to gauge how accurate a profiler is. With some results in the Java ecosystem, so now you know which profiler to pick there.

This is definitely true. Keep all this in mind when dealing with performance questions: design properly for the task, profile and profile some more, focus on the hotspots, keep things maintainable.

Nice simple fix in Git but with a large impact on backups. A good proof that profiling and keeping an eye on algorithmic complexity can go a long way in improving software.

Nice little article. It's a good way to point out that aiming for the lowest Big-O approach is often not what you want in terms of performance. Always keep the context in mind, and in doubt measure.

A quick tour of the available tools to profile Spring Boot applications.

Looks like an interesting little profiling tool. The article explains quite well how it's been done. Can be a nice blueprint to make other such tools.

Nice suite of tools. The eBPF based ones look promising.

Definitely to keep in mind when using sampling profilers indeed. They're useful, they help to get a starting point in the analysis but they're far from enough to find the root cause of a performance issue.

Nice reference for the tools available to profile software.

Very nice collection of stories from the trenches of Firefox development. Lots of lessons learned to unpack about optimizing for the right thing, tooling, telemetry and so on.

Or why using a profiler is not as easy as it sounds. This requires quite some experience and the ability to tap in other information not present in the profile.

The Rust tooling makes it super easy to profile your programs. This is neat.

Nice walk through for a use of PyO3 to make some Python code much faster. Nice to see how useful py-spy turn out to be in such scenarii as well.

Alright, that's an impressive set of tools they created to build their games. Lots of efforts went into this, very inspiring.

perf now available also to Python programs. This definitely can be useful for proper profiling.

Good explanation about how sampling works. Does a good job explaining why it shines and where it is limited.

One of the best developer tools around for analysis and profiling. I'm glad it exists, saved me a few times.

This looks like a very interesting tracing tool for debugging and profiling purposes.

That looks like a very interesting tool for larger Python based projects. Definitely need a way to profile memory use in there.

Good reminder on how a shared atomic can become a huge bottleneck in multi-CPU setups.