Is it possible to run multiple tensorflow serving containers on single GPU node kubernetes
Interesting question - as far as I know, this is not possible, also not for two containers running as the same pod (resources are configured on container level), at least not out of the box (see https://github.com/kubernetes/kubernetes/issues/52757)
I found this while searching for an answer: https://blog.ml6.eu/a-guide-to-gpu-sharing-on-top-of-kubernetes-6097935ababf, but that involves tinkering with kubernetes itself.
You could run multiple processes in the same container to achieve sharing, however this goes a bit against the idea of kubernetes/containers and of course won't work for 2 completely different workloads/services.