> However, in the meantime data science and machine learning continued to explode, and we found that customer interest in deploying machine learning models far outstripped demand for more conventional stream processing data algorithms.

My experience is quite similar : I either end up working with clients who are already using Spark etc, or they don’t have a mature data engineering lab. In both cases, deploying a model to production is always the most challenging.

I hope their MLOps strategy is better, than just binding to MLFlow. This tool is absolutely not ready for prime time, and plagued by bad product decisions.