Managing Access to Databricks SQL Endpoints

Question

Pulumi · Accepted Answer

To manage access to Databricks SQL Endpoints, we will utilize the Pulumi `databricks.SqlEndpoint` and `databricks.Permissions` resources from the `pulumi_databricks` package. The `SqlEndpoint` resource allows you to create and manage a Databricks SQL Endpoint, which is used to execute SQL queries on Databricks. The `Permissions` resource allows you to define access control for various Databricks resources, including SQL Endpoints.

Here is a step-by-step guide on how you can create an SQL Endpoint and manage access to it using Pulumi in Python:

1. **Install the Pulumi Databricks Provider**: Before you begin, you need to have Python and Pulumi installed on your machine. Then, you will install the Pulumi Databricks provider through pip.

```bash
    pip install pulumi-databricks
    ```

2. **Write the Pulumi Program**: We will now write a Pulumi program that creates an SQL Endpoint and assigns permissions to a specific group or user.

3. **Set Up the `databricks.SqlEndpoint` Resource**: This resource creates a new SQL Endpoint. You need to specify the necessary fields such as the name of the endpoint, cluster size, number of clusters, and data source ID.

4. **Set Up the `databricks.Permissions` Resource**: This resource manages the permissions for the SQL Endpoint. You specify the SQL Endpoint ID and define access controls (like which users or groups can access the endpoint and their permission levels).

Here is the Python program that performs these steps:

```python
import pulumi
import pulumi_databricks as databricks

# Step 1: Set up a new SQL Endpoint.
# Here you will replace the placeholder values with the appropriate settings for your Databricks environment.
sql_endpoint = databricks.SqlEndpoint(
    "my-sql-endpoint",
    name="my-sql-endpoint",
    cluster_size="Large",
    num_clusters=1,
    auto_stop_mins=120,
    data_source_id="YOUR_DATA_SOURCE_ID",
    # Enable Photon is an optional performance accelerator.
    enable_photon=True,
    # Additional attributes can be specified such as tags, warehouse type, etc.
)

# Step 2: Set up permissions on the SQL Endpoint.
# Replace 'some-user' and 'some-group' with real user or group names in your Databricks environment.
permissions = databricks.Permissions(
    "sql-endpoint-permissions",
    sql_endpoint_id=sql_endpoint.id,
    access_controls=[
        databricks.PermissionsAccessControlArgs(
            user_name="some-user",
            permission_level="CAN_MANAGE",  # CAN_MANAGE, CAN_USE, CAN_VIEW depending on required permissions
        ),
        databricks.PermissionsAccessControlArgs(
            group_name="some-group",
            permission_level="CAN_USE",
        ),
    ],
)

# Export the SQL Endpoint JDBC URL for use in applications.
pulumi.export("sql_endpoint_jdbc_url", sql_endpoint.jdbc_url)
```

Within this program, we:

- Create an SQL Endpoint with the desired configuration
- Grant permissions to a user to manage the endpoint and a group to use the endpoint
- Export the JDBC URL of the SQL Endpoint once it's created, so it can be used by your applications to connect to the endpoint

To apply these changes, you save the code in a file (e.g., `manage_sql_endpoint.py`), set up your Databricks environment and credentials as per Pulumi's setup instructions, and then run `pulumi up` from your terminal. This will start the Pulumi deployment process, and you'll see logs of the creation of the resources and outputs like the JDBC URL.

Please ensure that you have the correct Databricks workspace and authentication set up, as this code will only function in the context of a correctly authenticated and configured Pulumi Databricks environment.