DevOps Articles

Why does your Machine Learning Ops feel inadequate?

An early item in this list is about setting up CI/CD for the new service.

I consider how it eventually gets deployed to production and how it gets monitored post-deployment.

However, when I started the MLOps journey for our company, I realized that CI/CD of the kind practiced in software engineering is not a standard in Data Science practices.

This role is often used in the context of scaling the data that goes into the pipeline(ETL, Spark, etc) and not the ML model-related problems.

When this happened to us, we set forth in search of a provider who did MLOps out of the box.