I have a love/hate relationship with docker. On one side it's convenient to have a single line start for your services. On the other side as a self-hoster it made some developers rely only on docker meaning that deploying the stack from source is just an undocumented mess.
Also following the log4j vulnerability I tend to prioritize building from source as some docker package were updated far later than the source code was.
The Dockerfile is essentially the instructions for deploying from scratch. Sure, they most likely only exist for one distro but adapting isn't a huge chore.
You can also clone the repo and build the container yourself. If you want to update say, log4j, and then attempt to build it, that's still entirely possible and easier than from scratch considering the build environment is consistent.
I love Docker because it is the only sane method to selfhost shit with my Synology NAS, and I love my Synology NAS because it is the only Linux interaction that I have (from my old MacBook Pro).
Every time I hear this from one of my devs under me I get a little more angry. Such a meaningless statement, what are you gonna do, hand your pc to the fucking customer?
It's not actually meaningless. It means "I did test this and it did work under certain conditions." So maybe if you can determine what conditions are different on the customer's machine that'll give you a clue as to what happened.
The most obscure bug that I ever created ended up being something that would work just fine on any machine that had at any point had Visual Studio 2013 installed on it, even if it had since had it uninstalled (it left behind the library that my code change had introduced a hidden dependency on). It would only fail on a machine that had never had Visual Studio 2013 installed. This was quite a few years back so the computers we had throughout the company mostly had had 2013 installed at some point, only brand new ones that hadn't been used for much would crash when it happened to touch my code. That was a fun one to figure out and the list of "works on this machine" vs. "doesn't work on that machine" was useful.
You know what, this is on us. Chat GPT is just a prediction engine that tries to say what words it thinks follow a preceding prompt, and it’s looked at millions of examples (written by us) and it’s seen hapless clients and users complain about bugs and be told: “user error, works fine” so often chatGPT just thinks it’s just the culturally accepted polite response to a bug report, in the same way as responding to “thank you” with “you’re welcome”. This is a dark mirror on our profession.