I post this article because i think they did a very good job in describing why MLOps is complicated and what a real production pipeline for machine learning and AI should look like.
The creation of features and their versioning is a lot of work and it should be open to integration in more model experiments and applications.
On the other hand, we are always pushed to try new tools that create over-engineered systems that no one wants to use.