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Version: 1.37

Connect Azure Machine Learning

With the Azure Machine Learning integration, you can manage, monitor, and explain your Azure Machine Learning deployments in Deeploy.

Connect Azure Machine Learning

The Azure Machine Learning integration is controlled on team level. Admins can set up the integration on the Integrations page, which is part of the Admin panel. Click Connect on the Azure Machine Learning card to set up the integration.

Pre-requisites

An Azure Machine Learning workspace is required to be able to create deployments. Furthermore an Azure AD app is required which allows Deeploy to connect to your Azure Machine Learning workspace.

Making the integration

The following information is needed to set-up the Azure Machine learning integration:

  • Azure tenant ID, Azure subscription ID and Azure resource group name You can find these in the portal.
  • Azure client ID and Azure client secret Deeploy needs Azure AD app credentials to access the necessary resources on your Azure account. To get your Azure credentials, create an Azure client secret in your Azure AD app. Your app needs a role with the following minimal permissions:
"permissions": [
{
"actions": [
"Microsoft.MachineLearningServices/workspaces/environments/*",
"Microsoft.MachineLearningServices/workspaces/onlineEndpoints/*",
"Microsoft.MachineLearningServices/workspaces/models/*/read",
"Microsoft.MachineLearningServices/workspaces/read",
"Microsoft.MachineLearningServices/workspaces/metadata/*"
],
"notActions": [],
"dataActions": [],
"notDataActions": []
}
]

Get started with Azure Machine Learning for Deployments

You can get started with Azure Machine Learning Deployments by either making Azure Machine Learning your default Deployment backend, or creating single Azure Machine Learning Deployments. Both options are detailed in this section.

A guide to creating Deployments with Azure Machine Learning as a Deployment backend is available in Creating Azure Machine Learning Deployments.

Azure Machine Learning as your default Deployment backend

The default Deployment backend is controlled on a Workspace level. Workspace admins can change the default Deployment backend to Azure Machine Learning in the Workspace settings. All Deployments use the default Deployment backend, unless specified otherwise when creating a Deployment.

Create a single Azure Machine Learning Deployment

It's possible to create a Deployment using Azure Machine Learning, when the default Deployment backend is set to KServe or SageMaker (and vice versa). To change the Deployment backend for a single Deployment, untoggle the Use default backend settings toggle in the Deployment step when creating your Deployment, and choose Azure Machine Learning as your backend.