I run dnstools.ws which lets you perform DNS lookups, pings, traceroutes, etc. from 25 locations around the world. Each location is powered by a VPS running Debian, running a C# service that's compiled to native code ahead-of-time using Native AOT. It uses ~60MB RAM.
Six of the the locations are powered by tiny "NAT VPSes" (native IPv6 with shared NAT IPv4) that only cost a few dollars a year, sponsored by various server providers. These usually have 256 MB RAM and 4-5 GB disk space.
This is great with OpenVZ and LXC. Since they're containers that share the kernel with the host, kernel memory doesn't count towards the container's memory limit. I'm using ~75 MB RAM on those systems: ~60MB for the DNSTools worker and ~15MB for everything else (sshd, systemd, cron, rsyslogd, and unattended-upgrades). Plenty of room left.
I also have a few KVM systems with 256 MB RAM. These are what I'm struggling with.
Debian 13 (Trixie) increased the minimum hardware requirements from 256 MB to 512 MB RAM. It seems like this is a hard requirement - When running on a system using 256 MB RAM, the installer complains about having too little RAM, and OOMs during the installation. Even with a successful installation (e.g. upgrading from bookworm to trixie), it kernel panics on boot: "System is deadlocked on memory".
I could try debootstrap to bootstrap a basic system, or Clonezilla to clone a working disk image over the network, but I think I'd hit the memory deadlock too.
Does Debian have smaller kernel images for VM environments, that use less RAM? Or should I just give up on Debian for this use case?
Does anyone have a recommendation for another distro I should use? I've been considering trying Alpine. C# does support compiling to use musl instead of glibc, so that's not an issue. I'm also not tightly-coupled to systemd and can get rid of it.
I can mount a custom ISO on the systems, so booting from an ISO isn't an issue.
Thanks!
Edit: Alpine looks very promising - no issue installing it and running my app on a 256MB VM. This is probably what I'll end up using.


Accurate. At work I'm finally getting around to paying down tech debt from a temporary hack that was supposed to only be in the code for a month or so, but now it's been in our production code for around five years.
It would have been maybe a week or so to do it the right way initially, but we had hard deadlines and were pressed for time and just couldn't get around to doing it. Now it's over a month of work for one senior engineer (me) to clean up, because there's so many interdependencies between the hacky code and other parts of the system that depend on side effects of the hacky code, or the order of updates performed in the hacky code. What a mess.
At least AI can help a bit. Even the newest models aren't so great at system architecture in brownfield projects though (projects building into existing systems).