https://twitter.com/lstmeow/status/1442335775601741831?s=21
This is a good time to stop and reasses e.g.
https://miro.com/miroverse/mlops-stack-canvas/
What do you have, what do you need, what are the pain points etc.
Why should we expect more than 13% of data science projects to make it into production? Of course ML models can be used in production systems, but many projects are designed as one-off analyses to answer particular questions and don't need to be deployed or productionized.
After all, we have a few hundred years of history of people doing "data science" without the need for Spark or Kubernetes.