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Indeed, Kubernetes is hardly "light" :D However, it's only required when running pipelines in the cloud. When running locally (`$ sematic start`), nothing else
by neutralino1 4y ago
Indeed, Kubernetes is hardly "light" :D
However, it's only required when running pipelines in the cloud. When running locally (`$ sematic start`), nothing else than Python is required.
Regarding background, we are folks with experience building ML tooling. We've built infra around TF and Pytorch, but none with Jax. That being said, Sematic is agnostic to the framework you want to use.
- nemoniac 4y agoHow about if "locally" is a handful of servers reachable by ssh?
- neutralino1 4y agoYou can certainly deploy the web app on one server, and run your pipelines on another (or the same). In this case, "locally" would mean that the pipeline and all its steps run on the same host machine. This is totally sufficient in many cases. Kubernetes becomes interesting when using heterogeneous resources (e.g. GPU nodes for training, high-memory for data processing, etc.), but is not a necessity.