Multi-Server Real-Time Scoring with R

David Smith points out a reference architecture for real-time scoring with R distributed through Kubernetes:

Let’s say you’ve developed a predictive model in R, and you want to embed predictions (scores) from that model into another application (like a mobile or Web app, or some automated service). If you expect a heavy load of requests, R running on a single server isn’t going to cut it: you’ll need some kind of distributed architecture with enough servers to handle the volume of requests in real time.

This reference architecture for real-time scoring with R, published in Microsoft Docs, describes a Kubernetes-based system to distribute the load to R sessions running in containers.

Looks interesting.

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