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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. In your Databricks workspace, click the app switcher App icon. and select Databricks Apps.
  2. Click + Create app.
  3. In the Configure step, select an Instance size from the drop-down menu.
  4. Complete the remaining configuration steps and click Create app.

Edit app

To change the instance size for an existing app:

  1. In your Databricks workspace, click the app switcher App icon. and select Databricks Apps.
  2. Click the app name.
  3. Click the Settings tab.
  4. Under Compute, select a different Instance size from the drop-down menu.
  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.

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.
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