Due to the efficient diff'ing and data format, in practical terms I’d estimate a normal web app doesn’t require much more server resources with LV than a rest api backend. Maybe double? Of course that’ll depend drastically on the web page and template size used. Loading the text of full novels might not fair well!
On the extreme end I have a few pages that plot IoT data where it can take ~3 seconds to do a drop down in LV... Granted the server is serving a dozen SVG plots with a total of ~80,000 data points and performs the server template diff in that time. That’s on a RPi3 "server", which are also processing data, running similar pages on 4-10 browser tabs and running its own web browser. Haven't gotten close to using up the ram. Much of the slowness in that case is due to Chrome choking on that much SVG. I haven’t bothered optimizing the server side by dropping already rendered graphs.
Hope that helps give some insights. It'd be interesting to hear from people running high traffic sites.
On the extreme end I have a few pages that plot IoT data where it can take ~3 seconds to do a drop down in LV... Granted the server is serving a dozen SVG plots with a total of ~80,000 data points and performs the server template diff in that time. That’s on a RPi3 "server", which are also processing data, running similar pages on 4-10 browser tabs and running its own web browser. Haven't gotten close to using up the ram. Much of the slowness in that case is due to Chrome choking on that much SVG. I haven’t bothered optimizing the server side by dropping already rendered graphs.
Hope that helps give some insights. It'd be interesting to hear from people running high traffic sites.