Azure : Ansible role for deploying ML model integrated over databricks

Question

I have developed ML predictive model on historical data in Azure Databricks using python notebook. Which means i have done data extraction, preparation, feature engineering and model training everything done in Databricks using python notebook. I have almost completed development part of it, now we want to deploy ML model into production using ansible roles.

Answer 1

To deploy to AzureML you need to build the image from the MLflow model - it's done by using the mlflow.azureml.build_image function of MLflow. After that you can deploy it to Azure Container Instances (ACI) or Azure Kubernetes Service by using client.create_deployment function of MLflow (see Azure docs). There is also mlflow.azureml.deploy function that is doing everything in one step.

This blog post & example notebook that show the code for full process of training/testing/deployment of the model using MLflow & AzureML.