- The dash docs (https://plot.ly/dash) are itself a Dash app. They're getting a lot of traffic today with the launch and they're holding up OK to hundreds of active users.
- The state of Dash apps is entirely in the front-end (in JS in the web browser). The Dash app backend (the python part) is really lightweight - it's a flask server (that you run with an application server like gunicorn) that dispatches to the functions that you decorate. If your functions are really resource-intensive (in memory or if they block for a long period of time), then the app's performance will suffer as part of that. However, since this analytic code is scoped inside a function, the memory will free up after the request is done.
- Since Dash's callbacks are functional, you can pretty easily add caching. Caching will store the previously computed values and serve them if the input arguments are the same. There is some more info in the "performance" section of the docs: https://plot.ly/dash/performance