Databricks Apps environment

Your Databricks app runs in a managed environment with the following binaries and resources:

• Operating system: Ubuntu 22.04 LTS
• Python environment: Python 3.11, running in a dedicated virtual environment. All dependencies are isolated within this environment. Apps that use uv can specify a different Python version. See Manage dependencies for a Databricks app.
• uv version: 0.10.2
• Node.js environment: Node.js version 22.16. Manage dependencies using npm and package.json.
• System resources: By default, each app can use up to 2 virtual CPUs (vCPUs) and 6 GB of memory. Configure the compute size to adjust CPU and memory allocation based on your workload requirements. See Configure the compute size for a Databricks app.

View environment details

To view the environment for a specific app, including environment variables and installed packages, go to the Environment tab on the details page for the app. See View the details for a Databricks app.

Default environment variables

The following environment variables are available in every app:

Variable	Description
DATABRICKS_APP_NAME	The name of the running app.
DATABRICKS_WORKSPACE_ID	The unique ID for the Databricks workspace the app belongs to.
DATABRICKS_HOST	The URL of the Databricks workspace to which the app belongs.
DATABRICKS_APP_PORT	The network port the app should listen on.
DATABRICKS_CLIENT_ID	The client ID for the Databricks service principal assigned to the app.
DATABRICKS_CLIENT_SECRET	The OAuth secret for the Databricks service principal assigned to the app.

App telemetry environment variables

When you enable telemetry for your app, Databricks automatically configures the following environment variables in the app runtime:

Variable	Value	Description
OTEL_EXPORTER_OTLP_ENDPOINT	http://localhost:4314	The OTLP collector endpoint
OTEL_EXPORTER_OTLP_PROTOCOL	grpc	The export protocol
OTEL_RESOURCE_ATTRIBUTES	workspace.id=<id>,app.name=<name>	Resource attributes for trace context
OTEL_SERVICE_NAME	<your_app_name>	The service name for telemetry data
OTEL_BSP_MAX_QUEUE_SIZE	10000	Maximum span queue size
OTEL_BLRP_MAX_QUEUE_SIZE	10000	Maximum log queue size
OTEL_BSP_MAX_EXPORT_BATCH_SIZE	512	Batch size for span exports
OTEL_BLRP_MAX_EXPORT_BATCH_SIZE	512	Batch size for log exports
OTEL_BSP_SCHEDULE_DELAY	1000	Span export interval (ms)
OTEL_BLRP_SCHEDULE_DELAY	1000	Log export interval (ms)

To learn more about configuring app telemetry, see Configure telemetry for Databricks Apps.

Framework environment variables

The Databricks Apps runtime automatically sets port and host variables for supported Python frameworks. You don't need to configure these manually. All port variables are set to the value of DATABRICKS_APP_PORT.

Framework	Variables
Gradio	GRADIO_SERVER_PORT, GRADIO_SERVER_NAME=0.0.0.0
Streamlit	STREAMLIT_SERVER_PORT, STREAMLIT_SERVER_ADDRESS=0.0.0.0
FastAPI	UVICORN_PORT, UVICORN_HOST=0.0.0.0
Uvicorn	UVICORN_PORT, UVICORN_HOST=0.0.0.0
Flask	FLASK_RUN_PORT, FLASK_RUN_HOST=0.0.0.0
Dash	PORT
Express	PORT

Additional Streamlit environment variables

The runtime also sets the following Streamlit-specific variables:

Variable	Description
STREAMLIT_SERVER_ENABLE_XSRF_PROTECTION	Set to false. The Databricks Apps reverse proxy handles XSRF protection.
STREAMLIT_SERVER_ENABLE_CORS	Set to false. The Databricks Apps reverse proxy handles CORS.
STREAMLIT_SERVER_HEADLESS	Set to true so Streamlit runs without opening a browser window.
STREAMLIT_BROWSER_GATHER_USAGE_STATS	Set to false to prevent sending usage stats to Streamlit.

No Node.js libraries are pre-installed in the Databricks Apps environment. For Node.js apps, you must explicitly list all dependencies in your package.json file to ensure they are installed at runtime.