Minutes 2025-10-23

From MTU LUG Wiki
Revision as of 03:36, 24 October 2025 by D2wn (talk | contribs) (Created page with "# attendance dropped off this week ## always happens around this time of year # Lots of people run Jellyfin servers in their homelabs # Jellyfin by Allen! ## Over-the-top media services ## If you’ve used Netflix (and other streaming services) you’re probably used to to navigating these ## Hardware transcoding ### Typically used to downscale media from the base resolution to clients (e.g. 4K to 1080p) ### Dane cameo for anecdote about audio? #### Dane busy this week...")
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to navigation Jump to search
  1. attendance dropped off this week
    1. always happens around this time of year
  2. Lots of people run Jellyfin servers in their homelabs
  3. Jellyfin by Allen!
    1. Over-the-top media services
    2. If you’ve used Netflix (and other streaming services) you’re probably used to to navigating these
    3. Hardware transcoding
      1. Typically used to downscale media from the base resolution to clients (e.g. 4K to 1080p)
      2. Dane cameo for anecdote about audio?
        1. Dane busy this week :(
        2. Rozsa show about jazz
      3. x264 most supported but largest filetype
      4. AV1 smallest filetype but rarely supported (hardware decoding-wise) and computationally intensive
    4. Our jellyfin server
      1. Dell R730
      2. NVIDIA 1060 and 1070
      3. RAID 1 MDADM on two 500GB root disk SSDs
        1. ext4 as filesystem
      4. 14x 1.8TB 2.5” HDDs in a RAIDz2 (“RAID60”) ZFS pool with 16TB of total space
        1. probably overkill for our use
        2. Can download blender media at 4K res and do local LLMs for AI research which take a couple hundred gigs each
    5. Containers
      1. Podman can be used to manage services and allow updating without needing to update entire server or take down everything (e.g. like updating debian and needing to reboot to update kernel, and take down all running services)
      2. Our hope is to use for jellyfin and the frontend/backends for LLMs
    6. Jellyfin and NVIDIA setup
      1. Jellyfin hardware transcoding usage
      2. had to patch NVIDIA driver with a script off github to enable more than 2 transcodes per GPU
        1. NVIDIA moment
    7. RFFMPEG
      1. remote ffmpeg over a network, allows us to add GPUs to other servers and the jellyfin server to use them remotely if we ever need
    8. #arr suite
      1. just a suite of tools that take files and rename them for more easy indexing via Jellyfin
        1. Can be used in combination with our WIP automatic Blender movie downloader (coming #soon hopefully) to get auto-added to jellyfin
    9. Also allows auto-downloading media if you hook it up to things like a torrent tracker
      1. usually used for people running pirated media, not relevant for our case
    10. Jellyseer manages Jellyfin accounts and media requests/storage/quality
    11. Blender Open Studio films!
      1. By Blender Studios
      2. Blender is a FOSS 3D modelling software
      3. They make Public Domain short films to showcase Blender’s current capabilities
        1. Akin to Pixar’s short films
      4. They even used to allow you to download all the 3d assets used in the film
        1. Were also Public Domain, so you could use them in your own projects for whatever you want
      5. Our hope is too ‘mirror’ the films (so they’re not only on YouTube and proprietary sites)
        1. Like our mirrors server for open source Linux programs, but this one is for open media
    12. Selfhosting Jellyfin is also possible, and is what most people do
    13. Assigning accounts to users