General Performance Guidelines
Hardware and Software
Add more cores and memory: Regardless of whether you’re running Tableau Server on one computer or several, the general rule is that more CPU cores and more RAM will give you better performance. Make sure you meet the Tableau Server recommended hardware and software requirements.
If you are running Tableau Server in a virtual environment, use your VM host's best practices for vCPU allocation in relation to the number of physical CPU cores on the VM host.
Schedule refreshes for off-peak hours: Backup tasks tend to stall other background tasks until the backup is completed. Use the Background Tasks for Extracts administrative view to see your refresh and backup task schedules. Your refresh tasks should be scheduled for off-peak hours that don't overlap with your backup window.
Look at caching: Caching helps Tableau Server respond to client requests quickly, especially for views that connect to live databases. Confirm that Refresh Less Often on the Data Connections tab of the Configuration dialog box is selected.
Consider changing two session memory settings:
- VizQL session timeout limit: The default VizQL session timeout limit
is 30 minutes. Even if a VizQL session is idle, it is still consuming
memory and CPU cycles. If you can make do with a lower limit, use tabadmin to change
- VizQL clear session: By default, VizQL sessions are kept in memory even when a user navigates away from a view. This consumes a good deal of session memory. Instead, you can end sessions when users move away from a view by changing the value of the
true(the default is
Assess your process configuration: Tableau Server is divided into six different components called server processes. While their default configuration is designed to work for a broad range of scenarios, you can also reconfigure them to achieve different performance goals. Specifically, you can control on which computers the processes run and how many are run. See Performance Tuning Examples for general guidelines for one-, two-, and three-node deployments.