MLFlow is an open-source framework for registering, managing and tracking machine learning models. It is multiplatform, bringing consistent model training and model consumption across different platforms. This means, that training a model locally and uploading it to Azure or training a model on remote compute instances and downloading it, is a great feature for MLflow.
You can use MLflow with Azure CLI, Azure Python SDK or in the studio and it will deliver a consistent experience (note, some functionalities are limited to the language).
Click through for a quick overview of MLflow.