This is pretty rad! Thanks for sharing. I went down the same road with learning k3s on about 7 Raspberry Pis and pivoted over to Proxmox/Ceph on a few old gaming PCs / Ethereum miners. Now I am trying to optimize the space and looking at how to rack mount my ATX machines with GPUs lol… I was able to get a RTX 3070 to fit in a 2U rack mount enclosure but having some heat issues… going to look at 4U cases with better airflow for the RTX 3090 and various RX480s.

I am planning to set up Talos VMs (one per Proxmox host) and bootstrap k8s with Traefik and others. If you’re learning, you might want to start with a batteries-included k8s distro like k3s.

I followed the wiki tutorials for that. Make sure iommu is working, blacklist drivers on host, etc.

It’s on my lift of projects. I build a Proxmox+Ceph cluster and I have GPU passthrough working for LLM inference. I was planning to get docker headless Steam going and try to steam via Steam In Home Streaming as my first attempt then pivot to a full VM with Sunshine as a last resort.

FTFA:

hundreds of Android and iPhone apps with billions of downloads

I’m really not sure. I’ve heard of people using Ceph across datacenters. Presumably that’s with a fast-ish connection, and it’s like joining separate clusters, so you’d likely need local ceph cluster at each site then replicate between datacenters. Probably not what you’re looking for.

I’ve heard good things about Garbage S3 and that it’s usable across the internet on slow-ish connections. Combined with JuiceFS is what I was looking at using before I landed on Ceph.

I know Ceph would work for this use case, but it’s not a lighthearted choice, kind of an investment and a steep learning curve (at least it was, and still is, for me).

I went and edited my hosts file and added all of my devices, but I only have a handful. Tailscale on macOS has a lot of bugs, this being one of many.

Sorry but no there is no difference other than the words you use to describe them. Camera networks is surveillance.

I’ve used this in some bash scripts, very useful!

It depends on the container I suppose. There are some that are very difficult to rebuild depending on what’s in it and what it does. Some very complex software can be ran in containers.

I’ve been wanting to tinker with NixOS. I’ve stuck in the stone ages automating VM deployments on my Proxmox cluster using ansible. One line and about 30 minutes (cuda install is a beast) to build a reproducible VM running llama.cpp with llama-swap.

Typically, the container image maintainer will provide environment variables which can override the database connection. This isn’t always the case but usually it’s as simple as updating those and ensuring network access between your containers.

A lot of times it is necessary to build the container oneself, e.g., to fix a bug, satisfy a security requirement, or because the container as-built just isn’t compatible with the environment. So in that case would you contract an expert to rebuild it, host it on a VM, look for a different solution, or something else?

reproducing those installs from scratch + restoring backups would be a single command plus waiting 5 minutes.

Is that with Ansible or your own tooling or something else?

I wish we had fewer models of things. Drills, washers, vacuums, printers, etc. I get different features should cater to different audiences, but it’s taken to the extreme. Does one feature need to make a whole different model? If so, then I guess even the Tesla Model Y has different models - AWD, RWD, LR RWD (is that even still a thing?), Performance.

Gas stations adjust their pricing several times a day in some cases. For the record, I am against this hourly charge for EVs… maybe I’d be ok with it if the parking lot had a parking fee and the kWhs were gratis.

Ism’t that just automatic dynamic rate adjustment based on demand?

A typical data center rack holds about 40 servers, each with at least two networking interfaces. According to Boote, the Ethernet interfaces of a single rack draw 160 watts in total.

“Reducing the power draw of a data center, which may have hundreds or thousands of racks, would be akin to an energy savings of switching a building from incandescent to more energy efficient LED lighting and be well worth the investment,” he told LinuxInsider.

According to Boote, this optimization fixes a part of the kernel written when lower-speed Ethernet interfaces drew a fraction of today’s electrical needs. The networking stack design did not account for the growing power budget required by modern networking interfaces.

“By changing the priority of how the computers schedule tasks during high bandwidth events, a computer can better deal with networking traffic and prioritize energy expenditure in a way that makes sense for modern hardware and architectures,” he reasoned.

This is a feature that Jellyfin natively has already. So now Jellyfin exceeds Plex in some areas.