How does R handle model serving architecture in production environments?

R models are served via APIs using plumber, Docker, and orchestrated scaling layers.

Model serving decouples training and inference. R models are serialized (RDS or PMML) and loaded into stateless API containers. Load balancers distribute inference requests, while autoscaling handles traffic spikes.