Configure compute resources for a Databricks app

Each Databricks app runs on compute resources that determine its processing power and memory. Choose an instance size when you create or edit an app to match your workload requirements.

Available instance sizes

The following instance sizes are available for Databricks apps:

Size	CPU	Memory	Cost per hour	When to use
Medium	Up to 2 vCPUs	6 GB	0.5 DBU	Standard apps with moderate resource needs, such as dashboards, simple data visualizations, and forms. Most apps work well with this size.
Large	Up to 4 vCPUs	12 GB	1 DBU	Apps that process large datasets in memory, handle high concurrency, or perform more intensive computations.

If you don't specify an instance size, Azure Databricks assigns the Medium size by default.

Configure instance size

Configure the instance size when you create or edit an app.

Create app

To set the instance size when you create a new app:

1. Click Compute in the sidebar.
2. Go to the Apps tab.
3. Click Create app.
4. In the Configure step under Compute, select an instance size from the drop-down.
5. Complete the remaining configuration steps and click Create app.

Edit app

To change the instance size for an existing app:

1. Click Compute in the sidebar.
2. Go to the Apps tab and click the app name.
3. Click Edit
4. In the Configure step under Compute, select an instance size from the drop-down.
5. Click Save.

After you change the instance size, the app continues to run on the previous instance size until the update to the new instance size finishes. After the update finishes, the app switches over to the new size.

View the current instance size for an app on the Overview tab.

Best practices for instance sizing

When you choose an instance size for your app, consider the following best practices:

• Most apps work well with the default Medium size. Only choose Large if you encounter performance issues or know your app has high resource requirements.
• Test your app with the selected instance size in a development or staging workspace before you deploy it to production.
• Consider cost implications. The Large instance size costs more per hour.