bhramesh demonstrates how to use Azure Key Vault to securely retrieve database connection strings in Databricks notebooks, focusing on reducing vulnerabilities and improving workflow security.

Securely Managing Database Connection Strings in Azure Databricks with Key Vault

Database connection strings are sensitive assets and should never be exposed directly in Databricks notebooks. This guide walks you through storing and accessing these secrets securely using Azure Key Vault.

Why Use Azure Key Vault?

Azure Key Vault provides a secure mechanism for storing secrets such as database connection strings. Integrating Key Vault into your Databricks workflows reduces the risk of credential exposure and helps maintain a strong security posture.

Prerequisites

  • Azure App Registration: Ensure you have an app registered in Azure AD with permissions to read Key Vault secrets.
  • Tenant Id, Client Id, and Client Secret: Collect these from the registered app.
  • Key Vault Access Policies: Verify your app is granted get access to the secrets in Azure Key Vault.

Locating Required Information

  • Find Client Id and Tenant Id in your app registration overview.
  • Generate or retrieve Client Secret under Certificates & Secrets.
  • Go to Azure Key Vault > Access Policies to confirm your app’s permissions.

Databricks Notebook Setup

  1. Install Required Libraries
    • azure.keyvault
    • azure-identity
    • Ensure compatibility with your Databricks cluster configuration (see Databricks Docs).

  2. Import Necessary Modules

    from azure.identity import ClientSecretCredential
from azure.keyvault.secrets import SecretClient

  3. Initialize Credentials and Fetch Secrets Replace placeholders with your values:

    tenant_id = "<your-tenant-id>"
client_id = "<your-client-id>"
client_secret = "<your-client-secret>"
key_vault_url = "https://<your-key-vault-name>.vault.azure.net/"

credential = ClientSecretCredential(tenant_id, client_id, client_secret)
secret_client = SecretClient(vault_url=key_vault_url, credential=credential)

secret_name = "db-connection-string"
connection_string = secret_client.get_secret(secret_name).value
print(connection_string)
  4. Use the connection string to perform CRUD operations

Conclusion

By retrieving your database connection string from Azure Key Vault, your notebooks are cleaner, credentials remain protected, and your Databricks pipelines are production-ready and compliant.

Last updated: Dec 20, 2025 Version 1.0

Author: bhramesh

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