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Would you kindly share a tl;dr on what Monk GTR is?
ETA: its a pair of earbuds with a usb-c cable or dongle


Its the wrong question. workload matters far more than number of users.
1 user can be too many or 1000 just fine, depending on workload.


its a feature!


I feel like as soon as AI Agents calling businesses becomes common, a lot of people will simply hang up on them when they call.


Why do all of your posts read like an LLM wrote them?


I use ssh and the built in socks proxy for that ssh -D 1080 some_server will connect to the server and open a socks port on your local 1080 that exits via the server’s IP.


The usage is simple. If you name a quadlet (or systemd service unit file) with an @ in it then you can use it. Like foo@.container then anything you put between the @ and . is passed into the resulting unit file as %i.
So systemctl start foo@bar.service will pass ‘bar’ in where %i exists in the unit file. From there you can use it in a StartPreExec or whatever else to do instance specific stuff when the instance of the containerized service start.
Like ExecStartPre=/usr/local/bin/activate_config %i for example. A contrived example but hopefully you get the idea: with one quadlet file and a little scripting you can start many instances of a service that each automatically pull in their own configs.


I agree that ergonomics are also important, but for me not the top priority for me. For Podman, I like the way I can use Quadlet to quickly deploy and run containerized stuff.
However I really like it for building and running my own app stack pods. The combination of Quadlet and SystemD instance aliases is very powerful. I use this to drive all kinds of configuration automation.


Sounds like you are more interested in how the “house” was painted while I’m more focused on the construction materials and architecture.
If you truly don’t care what the source code looks like or how it works internally, then we aren’t even having the same conversation.


What do you mean by “clean design”?
If you are comfortable reading the source code for each project that is the most revealing way to see the difference.
In short, Docker has a lot more code because it duplicates a lot of kernel and systemd functionality (often poorly), uses multiple components that communication over grpc with each other to do things, requires setuid binaries, and defaults to running everything as root.
Podman, is a straight forward clean simple program that fully uses kernel and systemd interfaces rather than duplicating functionality. Quadlet is build on systemd generators and its use of templates via systemd instances lets you use deterministic dynamic configuration in ways that is unlike anything in Docker.


I think its more than Compose does a small subset of what Quadlets can do. I can understand why if your only use case is Compose and you already like it, why change? For me, the rootless by default and daemonless nature of podman quadlets, and its clean design all make it the preferred choice.


I don’t know how you would even compare them. Quadlets can do what Docker Swarm or Kube does with dynamic instances and dependency lifecycle management. Docker Compose doesn’t have nearly the same features as Podman Quadlet.


podman quadlets are next level
sorry i am a non-metronome owner and thus cannot relate


that’s the test
Going to migrate to infrastructure as code for my documentation
This is the way to do it. Using basic config management and never handjamming anything. I use the git commit log to make notes. That way, later I can check when a file was added or changed and see the explanation for it.


I wouldn’t be surprised if they were in on it. OpenAI wants us to think they have invented powerful beings that can do things like “escape containment” when its all BS.


Nice! got a link?
Also self-hosting doesn’t actually make you more attractive, and the people who promise it does are lying.