1. Using Databricks Tokens for Cross-Workspace Resource Sharing


    In this scenario, we're interested in setting up a Databricks environment that allows resources to be shared across Databricks workspaces. Databricks tokens are used to authenticate and are typically necessary when you want to set up automated or programmatic access to a Databricks workspace.

    A databricks.Token resource will allow us to create a personal access token. These tokens can be used, for instance, to authenticate API requests to Databricks workspace APIs or to set up automated access between workspaces without requiring interactive login credentials. It's important to note that tokens should be treated as sensitive data, as they grant access to your Databricks environment.

    Below is a Pulumi program that creates a Databricks token, which could then be used for cross-workspace resource sharing:

    import pulumi import pulumi_databricks as databricks # Creating a new Databricks token that can be used for API access or cross-workspace sharing. # The `lifetime_seconds` parameter defines the duration for token to remain valid. # In this example, we're setting it to a day (86400 seconds). # Please ensure to store the generated token value securely and use it responsibly, as it provides access to your Databricks workspace databricks_token = databricks.Token("my-databricks-token", lifetime_seconds=86400, comment="Token for cross-workspace access") # Export the ID of the token. Do NOT export the token value itself, as it is sensitive information. pulumi.export('token_id', databricks_token.id)

    Here's a step-by-step breakdown of the code:

    1. We import both pulumi and pulumi_databricks packages so we can use Pulumi's Python SDK and the Databricks provider to manage resources.

    2. We create a personal access token by instantiating the databricks.Token resource. We provide a lifetime_seconds parameter to determine how long the token will be valid. In this program, it is set to one day, but this can be adjusted to suit your needs.

    3. We add a comment to the token for easy identification within the Databricks workspace.

    4. Finally, we use pulumi.export to output the ID of the token. It is crucial to never export or print the token value itself as it should remain confidential to ensure the security of your resources.

    Remember that once you have the token, you'll need to use it to authenticate API requests. This typically involves adding it to a header in your HTTP request, like so:

    Authorization: Bearer <your-token-value>

    For more detailed information about managing Databricks tokens and other resources using Pulumi, refer to the databricks.Token documentation.

    Keep security in mind; always restrict the token's permissions to the minimum required to accomplish your goals, and rotate or expire them as often as practical. You'll want to store your token in a secure way, potentially using secret management tools that Pulumi offers, like Pulumi's built-in Secrets Provider.