A Machine Learning Engineer developed a dynamic pricing model in MLflow that requires values from the company's cloud database to generate predictions. At inference time the PyFunc model uses the cloud provider's Python SDK to retrieve the latest values from the database. The inference code works well in a notebook, but when the engineer deploys the model to Databricks Model Serving, they receive 401 errors saying the user is not authenticated when trying to access the database. The engineer deploys the code via the REST API with the following payload: Their Databricks administrators store cloud credentials under a Databricks secret scope called "cloud_creds" with key "db_key". These credentials can be used to authenticate to the cloud provider's SDK. Which change can the engineer make so the endpoint can authenticate to the remote database while avoiding storing the access tokens in plain text?
Select one answer.
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