1. Centralized Control of Database Connection Strings in Databricks


    Centralized control of database connection strings in Databricks can help ensure that sensitive information, such as credentials to databases, are managed securely and consistently across your Databricks workloads. Using Pulumi, you can automate the provisioning of secret scopes in Databricks, which can store such sensitive details.

    In Databricks, secret scopes are used to store secrets like database connection strings, API keys, and credentials so that they can be accessed securely from your Databricks notebooks, jobs, and other workloads. Pulumi's integration with Databricks allows you to define and manage these secret scopes as part of your infrastructure as code.

    Below is a Pulumi program written in Python that demonstrates how to create a Databricks secret scope and how to add a secret that contains a database connection string to the scope. Please note that this example assumes you have the Pulumi Databricks provider configured.

    import pulumi import pulumi_databricks as databricks # Create a new Databricks secret scope. # You can consider this as creating a container where you can store your secrets. # The 'initial_manage_principal' is set to 'users', which means all users can manage the secrets within the scope. secret_scope = databricks.SecretScope("db-connection-string-scope", initial_manage_principal="users") # Define the secret within the scope created. # Here we are storing a database connection string. # The 'string_value' field contains the sensitive information -- in this case, a connection string. # In a real scenario, you should fetch the connection string from a secure place, not hardcoded. database_connection_string = databricks.Secret("database-connection-string", key="dbConnectionString", string_value="Server=myServerAddress;Database=myDataBase;User Id=myUsername;Password=myPassword;", scope=secret_scope.name) # Export the name of the secret scope. This output will be shown after 'pulumi up' command is executed. pulumi.export("secret_scope_name", secret_scope.name)

    In the above code:

    • We create a new SecretScope resource, which is a Databricks secret scope.
    • Within the scope, we store a new secret (Secret) with a mock database connection string.
    • Finally, we export the secret scope name so it can be retrieved and used as required.

    Remember, you should never hardcode sensitive data like connection strings or passwords in your code. The placeholder connection string in the string_value argument above is just for demonstration. In a production scenario, retrieve the connection string from a secure location, like an environment variable or a secure vault, and inject it into your Pulumi program at runtime to maintain security best practices.