You have an Azure Machine Learning workspace named ML-workspace and an Azure Databricks workspace named DB-workspace, which contains a cluster named DB-cluster. You need to configure the environment so that MLflow metrics and artifacts from experiments run on DB-cluster are tracked to ML-workspace, while minimizing the amount of custom code required.

What should you you do?