I find a lot of these frameworks to be overkill.

A rating event comes into our web server (python), then sent to SQS, then the event is pulled by our custom artificial neural network (deep learning) script, --written in Go. A model is trained and serialized. Next, the serialized model is uploaded to Postgres where it is fetched by the web service (also written in Go) to serve predictions.

We update our models within 15 seconds of a user rating. Every month with millions of ratings, we re-train millions of models and serve billions of predictions.