[D] Offline batch serving

I‘m confused about how to serve a machine learning model for offline batch predictions.

Here’s what I thought of doing - creating a scheduled pipeline (with e.g. Airflow, Kubeflow, …) that generates the features and then loads the trained model from some object store (e.g. s3), generates the predictions and finally saves the them to a data warehouse ready to be consumed. That’s what makes the most sense to me.

However, some resources seem to recommend to deploy the model …

airflow features kubeflow machine machine learning machinelearning machine learning model object store offline pipeline predictions serve store them thought