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I'm currently hosting like 5 vms on a proxmox host (mostly ubuntu vms- pihole, nextcloud, home assistant, etc), which is an i5 4590 with 32 gb ram and I'm running up against the limits of how much ram I can provision and if 2 or more of my vms are doing something intensive at the same time I'm pinning the CPU. I don't think my use-case is that crazy for someone doing a little self-hosting.
Luxury! My homeserver has an i5 3470 with 6GB or RAM (yes, it’s a cursed 4+2 setup)!
Interesting, I also run Nextcloud and pihole, and vaultwarden, jellyfin, paperless-ngx, gitea, vscode-server and a minecraft server (every now and then).
You’re right that such a system really does show its age, but only when doing multiple intensive tasks at the same time. I try not to backup my photos to Nextcloud while running minecraft, for example, as the imagine identification task pins my CPU at 100%. So yes, I agree, you’re probably not doing anything out of the ordinary on your setup.
The point I was trying to make still stands though, as that pi 2B could run more than I would’ve expected beforehand. I believe it once even ran jellyfin, a simple file server, samba, and a webserver with a simple HTML website. Jellyfin worked just fine, as long as the pi didn’t have to transcode (never got hardware transcoding to work).
It is funny that you should run out of memory, seeing as everything fits (albeit, just barely) on my machine in 1/5 the memory. Would de overhead of running VM’s account for such a large difference?
I'm running the recognize app on nextcloud which I think requires at least 4-5 GB RAM, so I have 6 dedicated to that VM. I'm pretty sure the recommendation for Ubuntu in general was 2 GB RAM so I gave my pihole half that. Home assistant wanted 4 GB, but I gave it 2. I think my Jellyfin server has like 6 and I have another VM with like 4. So that's a total of like 19gb RAM provisioned. Plus I have a 2 TB zfs pool for my nextcloud VM. When I go into proxmox it tells me I'm using like 29.5 GB.
I suspect if someone was using docker or some other sort of containerization one could expect better performance than what I am getting with VMs.