Fresh Proxmox install, having a dreadful time. Trying not to be dramatic, but this is much worse than I imagined. I’m trying to migrate services from my NAS (currently docker) to this machine.

How should Jellyfin be set up, lxc or vm? I don’t have a preference, but I do plan on using several docker containers (assuming I can get this working within 28 days) in case that makes a difference. I tried WunderTech’s setup guide which used an lxc for docker containers and a separate lxc of jellyfin. However that guide isn’t working for me: curl doesn’t work on my machine, most install scripts don’t work, nano edits crash, and mounts are inconsistent.

My Synology NAS is mounted to the host, but making mount points to the lxc doesn’t actually connect data. For example, if my NAS’s media is in /data/media/movies or /data/media/shows and the host’s SMB mount is /data/, choosing the lxc mount point /data/media should work, right?

Is there a way to enable iGPU to pass to an lxc or VM without editing a .conf in nano? When I tried to make suggested edits, the lxc freezes for over 30 minutes and seemingly nothing happens as the edits don’t persist.

Any suggestions for resource allocation? I’ve been looking for guides or a formula to follow for what to provide an lxc or VM to no avail.

If you suggest command lines, please keep them simple as I have to manually type them in.

Here’s the hardware: Intel i5-13500 64GB Crucial DR5-4800 ASRock B760M Pro RS 1TB WD SN850X NVMe

  • curbstickle@anarchist.nexusEnglish
    2·
    22 hours ago

    It definitely is, especially if you get a cluster going. FWIW, my media is all on a synology NAS (well technically two, but one is a backup) that I got used through work, so your setup isn’t the wrong approach (imo) by any stretch.

    What it comes down to in the connection is how you look at it - with a VM, its a full fledged system, all by its lonesome, that just happens to live inside another computer. A container though is an extension of that host, so think of it less like a VM and more like resource sharing, and you’ll start to see where the different approaches have different advantages.

    For example, I have transcode nodes running on my proxmox cluster. If I had JF as a VM, I’d need another GPU to do that - but since its a container for both JF and my transcode node, they get to share that resource happily. Whats the right answer is always going to depend on individual needs though.

    And glad I could be of some help!