Broken link fixed

Author: pritamso

includes/machine-learning-mlflow-configure-auth.md

@@ -34,4 +34,4 @@ export AZURE_CLIENT_SECRET="<AZURE_CLIENT_SECRET>"
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 > [!TIP]
-> When working on shared environments, it is advisable to configure these environment variables at the compute. As a best practice, manage them as secrets in an instance of Azure Key Vault whenever possible. For instance, in Azure Databricks you can use secrets in environment variables as follows in the cluster configuration: `AZURE_CLIENT_SECRET={{secrets/<scope-name>/<secret-name>}}`. See [Reference a secret in an environment variable](/articles/databricks/security/secrets/secrets#reference-a-secret-in-an-environment-variable) for how to do it in Azure Databricks or refer to similar documentation in your platform.
+> When working on shared environments, it is advisable to configure these environment variables at the compute. As a best practice, manage them as secrets in an instance of Azure Key Vault whenever possible. For instance, in Azure Databricks you can use secrets in environment variables as follows in the cluster configuration: `AZURE_CLIENT_SECRET={{secrets/<scope-name>/<secret-name>}}`. See [Reference a secret in an environment variable](/azure/databricks/security/secrets/secrets#reference-a-secret-in-an-environment-variable) for how to do it in Azure Databricks or refer to similar documentation in your platform.