Solving Common Problems with Kubernetes
> What problem is k8s even trying to solve?> Say you want to deploy two Python servers. One of them needs Python 3.4 and the other needs Python 3.5.Honestly hilarious. The core value prop example is if you want to run two minor version different programming languages on one machine. In order to do that, you get to deploy and configure hundreds to thousands of lines of yaml, learn about at least 20 different abstraction jargon terms, and continue to spend all your time supporting this mess of infrastructure forever.How many engineering teams adopt kubernetes because it's what everyone's doing, versus out of genuine well-specified need? I have no idea.I use k8s at work, i know it has benefits, but it too often feels like using a bazooka to butter your toast. We don't deploy to millions of users around the globe, and we're all on one python version (for library compatibility, amongst other things). Docker is an annoying curse more than it's a boon. How much of this complexity is because python virtualenvs are confusing? How much would be solved if instead of "containers" we deployed static binaries (that were a couple hundred mb's larger apiece because they contained all their dependencies statically linked in... but who's counting). Idk. Autoscheduling can be nice, but can also be a footgun. To boot, k8s does not have sane defaults, everything's a potential footgun.In 10 years we're going to have either paved over all of the complexity, and k8s will be as invisible to us then as linux (mostly) is today. Or, we'll have realized this is insanity, and have ditched k8s for some other thing that solves a similar niche.edit: I realize this is a salty post. I don't mean to make anyone feel bad if they love to think about and use k8s. I appreciate and benefit from tutorial articles like this just as much as the next dev. It's just the nature of the beast at this point, I think.