Coming from someone who started selfhosting on a pi 2B (similar-ish specs), you’d be surprised. If you don’t need anything fast or fancy, that 1GB will go a long way, and plenty of selfhosted apps require very little CPU. The only real problem I faced was that all HTTPS-related network tasks were limited at ~3MB/s, as that is how fast my pi could encrypt the data (presumably, I just saw my webserver utilising the entire CPU and figured this was the most likely explanation)
I’ve had good experiences with whisper.cpp (should be in the AUR). I used the large model on my GPU (3060), and it filled 11.5 out of the 12GB of vram, so you might have to settle for a lower tier model. The speed was pretty much real time on my GPU, so it might be quite a bit slower on your CPU, unless the lower tier models are also a lot faster (never tested them due to lack of necessity).
The large model had pretty much perfect accuracy (only 5 or so mistakes in ~40 pages of transcriptions), and that was with Dutch audio recorded on a smartphone. If it can handle my pretty horrible conditions, your audio should (hopefully) be no problem to transcribe.
It depends what you’re optimising for. If you want a single (relatively small) download to be available on your HDD as fast as possible, then your current setup might be better (optimising for lower latency). However, if you want to be maxing out your internet speeds at all time and increase your HDD speeds by making the copy sequential (optimising for throughput), then the setup with the catch drive will be better. Keep in mind that a HDD’s sequential write performance is significantly higher than its random write performance, so copying a large file in one go will be faster than copying a whole bunch of random chunks in a random order (like torrents do). You can check the difference for yourself by doing a disk benchmark and comparing the sequential vs random writes of your drive.
qBittorrent has exactly the option you’re looking for, I believe it’s called “incomplete download path” in the settings, letting you store incomplete downloads at a temporary path and moving them to their regular location when the download finishes. Aside from the download speed improvement, this will also lead to less fragmentation on your HDD (which might be part of the reason why it is so slow when downloading directly to it). Pre-allocating space could have the same effect, but I would recommend only using one of these two solutions at once (pre-allocating space on your SSD would only waste space)
I have about 0 experience with openssl, I just looked at the man page (openssl-enc). It looks like this command doesn’t take a positional argument. I believe the etcBackup.key file isn’t being read, as that command simply doesn’t attempt to read any files without a flag like -in or -out. I could be wrong though, see previously stated inexperience.
Dutch media are reporting the same thing: https://nos.nl/l/2529468 (liveblog) https://nos.nl/l/2529464 (Normal article)
Luxury! My homeserver has an i5 3470 with 6GB or RAM (yes, it’s a cursed 4+2 setup)! </badMontyPythonReference>
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?