Sharded in-memory caching turns out to be rather useful at scale :)
Some of the key examples highlighted on our blog are Unity Catalog, which is essentially the metadata layer for Databricks, our Query Orchestration Engine, and our distributed remote cache. See the blog post for more!
I'm not sure if this is what you meant, but the website certainly doesn't call out to LLMs under the hood! Agreed, that would be a terrible idea. LLMs were just used to help write the code for the site, tweaked my post to clarify.
I was looking for a VS Code extension precisely like this, and after plenty of searching I managed to find it. Given how polished it is, definitely deserves to be better known. And of course FOSS to boot!
I'm afraid that's not supported today. But it looks like kprobes do support offsets within a function, so it should be possible to get it to work. That does sound pretty cool, please open an issue for this if you're interested! It might be as simple as (effectively) s/uprobe/kprobe/g, in which case I can try to get that working.
As jpgvm mentioned, yes Rust is a compiled language so it works well with eBPF!
The full picture is always a bit nuanced though so to expand on that: I have tried it cursorily with rust [using wachy to trace wachy :)] and it appears to work. The one issue I would say is that wachy is currently hardcoded to use C++ symbol demangling, so rust function names are not completely accurate (although it's surprisingly decent) - please open an issue if you want that fixed (or if you run into any other issues)! I decided it's better to get it out there and improve things that people actually use rather than fix all my TODOs (excuses for being lazy).
And with rust async, I haven't tried it myself but looked into the details some time back. Wachy works by simply looking at function entry/exit timestamps, but the rust aysnc impl is using futures + poll rather than saving and restoring stacks, so it's not gonna work. You can presumably trace the future's poll function, which may or may not be useful. Although, perhaps with some custom eBPF logic and examining the poll return value it could be made to work...
Thanks! Fair point about the naming - as they say, there are only two hard things in computer science: cache invalidation and naming things (and off-by-one errors). My personal view is that everyone should be free to pronounce things as they like (e.g. gif) but I didn't realize the implications for sharing and adoption.
Some of the key examples highlighted on our blog are Unity Catalog, which is essentially the metadata layer for Databricks, our Query Orchestration Engine, and our distributed remote cache. See the blog post for more!