It's also essential that shiny app developers optimize their applications as necessary to ensure the end users of their applications have as good an experience using them as possible. However, even a 2 CPU machine can handle the 6 simultaneous connections, albeit with some delay to the user:įor the most part, the default settings will work fine, but it's important to remember that allocating more processes (ie CPU and RAM) to an overloaded and poorly performing shiny app is only half a solution.Notice in this recording how the CPU indicator goes into the red very quickly, as each shiny connection puts a new demand on the database.This feature is called the "Utilization Scheduler"ĭemo on the instructor server where and how to change the settings for an app. For this reason, RStudio Connect is able to run multiple instances of the same app and spread visitors across those instances. Multiple users can connect to a single R process.Įventually, though, the load on a single R process will become too high fo Shiny to respond to user requests in a timely fashion. Now turn your attention to the second large topic: Scaling your Shiny apps.
However, identical environments are not necessary. Multiple connections per R process in a Shiny appĬustomers often use kerberos in this scenario Deploying #Ĭonsistency between dev and prod environments is critical! The RStudio professional database drivers 3.3 RStudio Workbench Startup and packages
0 kommentar(er)
