Yep, bind mount the data and config directories and back those up. You can test a backup by spinning up a new container with the data/config directories.
This is both easy and generally the recommended thing I’ve seen for many services.
The only thing that could cause issues is breaking changes caused by the docker images themselves, but that’s an issue regardless of backup strategy.
Yeah, that would be my recommendation too. Anything else will produce a worse experience (laggy and slow) and more complexity to get setup/maintain.
Some of the commands I use a lot for debugging containers, in case you go down that route:
docker run --rm -it --entrypoint bash <image_name>docker exec -it <container_name>Once you know how to use docker/containerization it’ll be the only way you want to deploy applications. Most popular applications will also have good guides on how to setup/config the container, but sometimes you’ll need to read up on docker and Linux to figure things out.
For me, it’s worked out for plex. What it offered at the time was more than worth the price and I’ve felt a little bad about it being a once and done payment.
That being said they’ve hurt some of the good will with the changes they’ve made, but also I imagine they’re struggling to find a sustainable path for development.
I think the easiest way would be to have two vlans on your local network. One that is connected to the internet and another that is local only. I think you’d have to switch networks when wanting to access the jellyfin server in that instance, but would negate the main issue, which is your VPN.
Edit: that’s about the most secure you can get I think. If you bought a different physical router to host it, you’d have about as secure a setup as possible.
Third prong, looking constantly for new information. Yeah, most of these sites may be basically static, but it’s probably cheaper and easier to just constantly recrawl things.
I keep expecting something, the lifetime pass has more/less paid for itself.
That being said, they do still offer the lifetime pass, so clearly they see it as worth it.
Samba Bamba!!
Also, whether you see it as a plus or minus, windows wsl defaults to Ubuntu. So, msoft also seems to be somewhat invested in them long term.
Plex and plexamp is the best music hosting setup I’ve found too. Users can have their own playlist and there is some smart playlist generation.
They also had (maybe still have) tidal integration.
However, you’ll still be relying on other services (probs spotify/etc.) to find new things.
I’ve tried the AIO container. The issue I’ve had is that I already have a file system for documents and try to attach it as a network drive, it’s at this point everything falls apart (not to mention just generally slow performance).
Sorry I can’t really help, but can commiserate. Nextcloud is the one service I’ve never gotten to run right. Not sure if its gotten any better but a year or two ago I was trying and just wasn’t getting consistent results from it.
I commented further up, but will add here. I also have a Go 1 and Ubuntu worked okay. Webcam was definitely a no go, but it ran well enough for some productivity and light gaming.
Only thing I really hate is hibernate doesn’t really work on Linux. For a tablet, maybe you always keep yours on, but I liked hibernate to help keep the battery going longer.
Commenting to add here, this is not going to be about distro choice as much as seeing what configuration on the Linux-surface guide provides greatest support.
There are many things that may not work on your surface due to support, so definitely follow those guides.
Spent hours trying to get the Webcam to work on Surface Go 1.
I’m not sure how good a source it is, but Wikipedia says it was multimodal and came out about two years ago - https://en.m.wikipedia.org/wiki/GPT-4. That being said.
The comparisons though are comparing the LLM benchmarks against gpt4o, so maybe a valid arguement for the LLM capabilites.
However, I think a lot of the more recent models are pursing architectures with the ability to act on their own like Claude’s computer use - https://docs.anthropic.com/en/docs/build-with-claude/computer-use, which DeepSeek R1 is not attempting.
Edit: and I think the real money will be in the more complex models focused on workflows automation.
My main point is that gpt4o and other models it’s being compared to are multimodal, R1 is only a LLM from what I can find.
Something trained on audio/pictures/videos/text is probably going to cost more than just text.
But maybe I’m missing something.
My understanding is it’s just an LLM (not multimodal) and the train time/cost looks the same for most of these.
I feel like the world’s gone crazy, but OpenAI (and others) is pursing more complex model designs with multimodal. Those are going to be more expensive due to image/video/audio processing. Unless I’m missing something that would probably account for the cost difference in current vs previous iterations.
Looks like there is a config and cache location in their docker scripts. The easiest way to make a docker application portable is to bind mount the config and cache. That way you have access to the actual files and could copy them to your windows partition.
If you’re already using a volume for that data, I think it becomes a bit trickier. I know technically you can move or copy volumes, but I’ve never tried. Although you could still bind mount a random directory and still copy the files out.