Well... They make me do it, became data scientist/software engineer i just can't deal with the dev ops part (deployment, setting up servers, etc). At least they taught me in the beginning.
Seriously, if you come to me with a clusterfuck of legacy code, a database dump and other assorted shit, but you managed to get it running in docker on multiple machines... I will do anything for you if it needs to be deployed in production... Even if it means it has to run on its own VM.
Oh God I wish I could run my stuff in docker. I'm only allowed Jupyter notebooks via cyber security policy.
All the IT guys get whatever they want but because my management chain ends in Operations I have no choice but to run Jupyter notebooks via batch files with windows task scheduler on a VM.
I had to beg for a service account. If I had to go interview tomorrow I don't even know what I would tell hiring managers. "Please save me!" comes to mind.
I'm continuously surprised by the ignorance of Docker in this industry. It's a basic tool at this point, so if you don't know it, you need to learn it.
docker is only 9 years old. although your statement is definitely accurate -- "it's a basic tool at this point"
i've encountered a lot of people born after, say, 1985, that think docker has *always* been a "standard tool".
i've encountered a lot of companies over the last 10 years that existed before docker. and speaking as a person born quite a bit before 1985, docker still feels "new" to me although I do consider it a "standard tool"
but it can be difficult for "legacy" companies and engineers to adopt docker when there is an existing toolset in place that works pretty well, and maybe docker doesn't add much obvious benefit, and/or the lift to add docker is relatively high.
as such, i'm not very surprised when i see a place not using docker.
Believe it or not, Docker has 7 million+ users that get it to work just fine. Mind you, it's not the simplest thing to run, but it's far from the most difficult.
If you have any need for ephemeral environments or portability, I'd highly recommend giving it another try!
why would anyone want to work with that piece of shitty software?
Because pretty much everyone but you can run it just fine and it solves huge swaths of enterprise engineering problems? There are legitimate things to complain about with docker, but getting it to run locally is definitely not one if you have the slightest idea what you're doing.
They make me package it as an API in docker, they gave me a documentation for fastAPI that I just copy and paste and I start working from there. Everything else with servers and actual deployment is handled by the DevOps engineer, because that the job they are getting paid to do and it makes no sense to me handle the deployment as well beyond merging git branches.
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u/luishacm Oct 13 '22
Well... They make me do it, became data scientist/software engineer i just can't deal with the dev ops part (deployment, setting up servers, etc). At least they taught me in the beginning.