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The following describes the system environment in which your Databricks app runs:
- Operating system: Ubuntu 22.04 LTS
- Python environment: Python 3.11, running in a dedicated virtual environment. All dependencies are isolated within this environment, including libraries defined in
requirements.txtand pre-installed libraries. - Node.js environment: Node.js version 22.16. Manage dependencies using
npmandpackage.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, Azure 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.
Default environment variables for Streamlit
If you use the Streamlit framework, the Databricks Apps environment pre-configures several Streamlit-specific environment variables:
| Variable | Description |
|---|---|
STREAMLIT_SERVER_ADDRESS |
The server address for use by Streamlit. This value is set to 0.0.0.0 and must not be overridden. |
STREAMLIT_SERVER_PORT |
The port for use by Streamlit. This value is set to DATABRICKS_APP_PORT and must not be overridden. |
STREAMLIT_SERVER_ENABLE_XSRF_PROTECTION |
Because the Databricks Apps reverse proxy protects against Cross-Site Request Forgery (XSRF), this is set to false. |
STREAMLIT_SERVER_ENABLE_CORS |
Because the Databricks Apps reverse proxy protects against Cross-Origin Resource Sharing (CORS), This is set to false. |
STREAMLIT_SERVER_HEADLESS |
This is set to true so Streamlit runs without opening a browser window when starting. |
STREAMLIT_BROWSER_GATHER_USAGE_STATS |
This is set to false to prevent sending user stats to Streamlit. |
Pre-installed Python libraries
The following Python libraries are pre-installed in the Databricks Apps environment. You don’t need to include them in your app unless you require a different version.
| Library | Version |
|---|---|
| databricks-sql-connector | 3.4.0 |
| databricks-sdk | 0.33.0 |
| mlflow-skinny | 2.16.2 |
| gradio | 4.44.0 |
| streamlit | 1.38.0 |
| shiny | 1.1.0 |
| dash | 2.18.1 |
| flask | 3.0.3 |
| fastapi | 0.115.0 |
| uvicorn[standard] | 0.30.6 |
| gunicorn | 23.0.0 |
| huggingface-hub | 0.35.3 |
| dash-ag-grid | 31.2.0 |
| dash-mantine-components | 0.14.4 |
| dash-bootstrap-components | 1.6.0 |
| plotly | 5.24.1 |
| plotly-resampler | 0.10.0 |
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.