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Copy file name to clipboardExpand all lines: articles/machine-learning/how-to-setup-mlops-azureml.md
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@@ -63,7 +63,7 @@ Before you can set up an MLOps project with AzureML, you need to set up authenti
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1. If prompted, choose **Bash** as the environment used in the Cloud Shell. You can also change environments in the drop-down on the top navigation bar
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1. Copy the bash commands below to your computer and update the **projectName**, **subscriptionId**, and **environment** variables with the values for your project. If you are creating both a Dev and Prod environment, you'll need to run this script once for each environment, creating a service principal for each. This command will also grant the **Contributor** role to the service principal in the subscription provided. This is required for Azure DevOps to properly use resources in that subscription.
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@@ -116,7 +116,7 @@ Before you can set up an MLOps project with AzureML, you need to set up authenti
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1. Select Contributor and add members selecting + Select Members. Add the member **Azure-ARM-Dev-ProjectName** as create before.
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1. Repeat step here, if you deploy Dev and Prod into the same subscription, otherwise change to the prod subscription and repeat with **Azure-ARM-Prod-ProjectName**. The basic SP setup is successfully finished.
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2. Select **create a new project** (Name the project `mlopsv2`for this tutorial).
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3. In the project under **Project Settings** (at the bottom left of the project page) select**Service Connections**.
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4. Select **New Service Connection**.
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5. Select **Azure Resource Manager**, select**Next**,select**Service principal (manual)**, select**Next** and selectthe Scope Level **Subscription**.
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