I've been reading up on MLOps. I attended talks and enrolled to Coursera Machine Learning Engineering for Production (MLOps) Specialization.

But the best source so far has been the book "Builing Machine Learning Pipelines". It's a treasure of practical and applicable methods to build different kinds of ML pipelines. But since it's focused on Tensorflow Extended it's restricted to that environment.

It states that it's planned that Tensorflow Extended will be agnostic in the future. And even if you don't use Tensorflow, there are still many good priniples in the book that can be migrated to other tools.

Definitley worth a read!