Sort of. My thinking is that the input to define the workflow should be anything you prefer to use (TS, Go, YAML, etc.) and the orchestrator's job is to model that and execute the job, given your deployment model.
I'm mainly looking at Rust based projects and haven't been able to find something to use out of the box, without hacky RPC/Shell execs. Curious if you have any suggestions?
The big data world largely revolves around python, like much of the AI world. Many of the people are more focused on the science than programming, so they aren't interested in the same arguments we often see about rise being a good choice for implementation. They want to use a language they know well to get their job done, hence something like Airflow be asked about in other comments.