Badabinski

Manjaro isn’t Arch. Doesn’t use the same repos.

This mirrors my experience. I -Syu on a weekly basis, spend about 3 minutes doing pacnews, and then I’m done.

Only possible AI thing I see is .zed in the .gitignore, but that’s not an indicator of LLM usage. Plenty of people use zed with all AI features disabled.

I’ll agree that list comprehensions can be a bit annoying to write because your IDE can’t help you until the basic loop is done, but you solve that by just doing [thing for thing in things] and then add whatever conditions and attr access/function calls you need.

Anubis has worked if that’s happening. The point is to make it computationally expensive to access a webpage, because that’s a natural rate limiter. It kinda sounds like it needs to be made more computationally expensive, however.

Do you have any sources for the 10x memory thing? I’ve seen people who have made memory usage claims, but I haven’t seen benchmarks demonstrating this.

EDIT: glibc-based images wouldn’t be using service managers either. PID 1 is your application.

EDIT: In response to this:

There’s a reason a huge portion of docker images are alpine-based.

After months of research, my company pushed thousands and thousands of containers away from alpine for operational and performance reasons. You can get small images using glibc-based distros. Just look at chainguard if you want an example. We saved money (many many dollars a month) and had fewer tickets once we finished banning alpine containers. I haven’t seen a compelling reason to switch back, and I just don’t see much to recommend Alpine outside of embedded systems where disk space is actually a problem. I’m not going to tell you that you’re wrong for using it, but my experience has basically been a series of events telling me to avoid it. Also, I fucking hate the person that decided it wasn’t going to do search domains properly or DNS over TCP.

Debian is superior for server tasks. musl is designed to optimize for smaller binaries on disk. Memory is a secondary goal, and cpu time is a non-goal. musl isn’t meant to be fast, it’s meant to be small and easily embedded. Those are great things if you need to run in a network/disk constrained environment, but for a server? Why waste CPU cycles using a libc that is, by design, less time efficient?

EDIT: I had to fight this fight at my job. We had hundreds of thousands of Alpine containers running, and switching them to glibc-based containers resulted in quantifiable cloud spend savings. I’m not saying musl (or alpine) is bad, just that you have horses for courses.

Is it? I thought the thing that musl optimized for was disk usage, not memory usage or CPU time. It’s been my experience that alpine containers are worse than their glibc counterparts because glibc is damn good. It’s definitely faster in many cases. I think this is fixed now, but I remember when musl made the python interpreter run like 50-100x slower.

EDIT: musl is good at what it tries to be good at. It’s not trying to be the fastest, it’s trying to be small on disk or over the network.

The one where every LLM-generated shell script I read is another deep splinter in my fingernail quick that I have to rip out and destroy because it’s a godfucked mess of bad practices that we can never ever ever ever EVER train out of an LLM at this point.