What if you're on a hosted service like gke/aks? The work needed to maintain the system has been minimal for us with a lot of positives
Yes, it probably is overkill for your 10req/s app, granted. But I highly advise everyone to at least give it a try out of curiosity, because a lot of hard problems at medium scale and above just go poof with K8s.
No, they don't? I don't know why anybody would just assume that something as complex as kubernetes would just run flawlessly once you actually try to run it on thousands of servers. Must be something to do with google PR because people definitely don't seem to assume the same for e.g. hadoop or openstack. Make a guess at how many people large companies have to employ to actually keep their smart cluster scheduler running?
>when I started my new job on a 22 node GKE cluster
>problems at medium scale
vs
>Make a guess at how many people large companies have to employ to actually keep their smart cluster scheduler running
K8s obviously is not a silver bullet and of course there's ops work to be done. I can't comment on whether operating K8s clusters in other contexts makes economic sense, but I know it does for our current team.
But the reason for that is not that it makes "hard problems go poof at scale". The reason is that you're using a hosted service where somebody else (in this case, Google themselves) takes care of the problems for you for a fee and - at small scale - you only have to pay them a fraction of a single operation's engineers salary for it.
So of course it makes economic sense for you to use a hosted service where the sharing economy kicks in, but your recommendation to use kubernetes because it solves hard technical problems at medium scale does not follow from that.
Even if they had, it doesn’t justify your aggression. Maybe take a break from the internet for a bit to clear your head.
GKE's services are, as far as I can tell from their pricing page[0], free. The compute running on top of GKE is charged at the GCE rate, the master node spun up by GKE is free.
Disclaimer: I work at Google Cloud, but nowhere near these offerings.
As to why they're taking the loss on the master node VM, I don't know. I had previously expected that it was a cost and was quite frankly pleasantly surprised that it wasn't - it seems like the most obvious sell. If I had to guess as to why it's not my best assumption would be that there's far more to be gained in getting companies comfortable with scaling and from angles that go beyond just the strict monetary benefit of them going from 3 compute instances to 300.
Much different use-case than most, though: automated machine learning pipelines via Pachyderm [1]. Would never have touched K8's if it wasn't for Pachd, and between their layer and GKE it's been quite painless. May have given up on Pachyderm if it wasn't for GKE; we're not cut out for maintaining K8's, and our first shot on AWS (pre-AKS) was not pretty.
tl;dr: K8's are great when it's all but completely abstracted away from you