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Joined 1 year ago
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Cake day: June 19th, 2023

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  • The good thing about Linux is, it’s not very ressouce demanding. If you pick the xfce version of Mint, you can get away with 4GB of RAM. But you won’t have that much fun coding as soon as you start something more ressource heavy (big data sets, ML, …) so this depends a little in which direction you want to go. However see if you can find something used, preferably something you can open from the back side to upgrade components like SSD and RAM (cheaper than buying higher specs)










  • thisNotMyName@lemmy.worldtoMildly Infuriating@lemmy.worldGood enough
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    1 year ago

    Not a single sidewalk is built to last the weight of a car. They are build as cheap as possible (sand bed + stones), because they are not supposed to get exposed to heavy loads. That’s why they are often in bad conditions, they usually don’t even have tree root protection, so they get regularly misformed from below and above





  • Don’t worry, most of this is about learning :) You could also put Docker on the Linux, install Jellyfin as a Docker container, and only fore it up when you are using Jellyfin. It’s a little less convenient, than having it available all the time, but storing all media in H264 AC3 (most common video and audio codecs) costs a lot of storage (H265 and AV1 are far more efficient). Another pro of Docker is, when you decide to move your server, you just shut down the container, copy it’s data and start the container on the new device



  • I’d go for the consumer case with as much drive space as possible, but in the end it’s up to your taste. With rackmount full professional server stuff, you have to keep in mind, it’s not only quite large in terms of space, but also noisy. This is something for the basement or something. Another option would be a mini pc like a NUC combined with a NAS - here is the limit the upgradability of the hardware. Like you can usually upgrade the RAM a little and the system drive, but that’s it. Especially for media stuff (Plex, Emby, Jellyfin) it can be interesting to have a dedicated GPU, like an Intel card, to have more transcoding capabilities. I’m currently running most things from a SFF PC, but also have a Pi and an old laptop in use for various tasks (main reason is lazyness to move the services to the SFF lol)