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.

Related Posts

Timing R Function Calls

Colin Gillespie shows off an R package for benchmarking: Of course, it’s more likely that you’ll want to compare more than two things. You can compare as many function calls as you want with mark(), as we’ll demonstrate in the following example. It’s probably more likely that you’ll want to compare these function calls against more […]

Read More

Creating Containers and Volumes

Grant Fritchey continues a dive into containers. First up is running a Docker container: Let’s break this down a bit so you know what you just did. The two ‘-e’ statements are setting environment variables. The first is accepting Microsoft’s end user license agreement, EULA. The second is setting the SA password. By default, we’re […]

Read More


March 2019
« Feb Apr »