This is a fantastic question. Unfortunately, the answer is usually pretty dependent on the type of work that R users on your server will be doing. It is important to keep in mind that:
- R is memory intensive and often copies on reference (i.e. a 10GB dataset could be expected to use 20GB+ of RAM)
- R is generally single threaded (although there are packages that expand this functionality)
We do have an app available that tries to provide a general rule of thumb here: https://gallery.shinyapps.io/instanceCalc/
If you would like to discuss the item with someone, our Customer Success or Solutions Engineering teams would be happy to do so. We usually recommend picking a general size based on the best available estimate and then:
I hope that helps! Any remaining questions that we can assist with? Since you mention load balancing, I want to be clear that load balancing of RStudio Server Pro is usually an
active-passive setup. It is possible to enable fail-over if the master node goes down, but traffic should only be routed to one node at a time. RStudio Server Pro will take care of routing R sessions to the most desirable node using your chosen balancing method.