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Update articles/machine-learning/how-to-autoscale-endpoints.md
Co-authored-by: Mope Akande <[email protected]>
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articles/machine-learning/how-to-autoscale-endpoints.md

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@@ -25,7 +25,7 @@ Today, you can manage autoscaling using either the Azure CLI, REST, ARM, or the
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## Prerequisites
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* A deployed endpoint. [Deploy and score a machine learning model by using an online endpoint](how-to-deploy-online-endpoints.md).
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* To use autoscale, the role `microsoft.insights/autoscalesettings/write` must be assigned to the identity that manages autoscale. You can use any built-in or custom roles that allows this action. For general guidance on managing roles for Azure Machine Learning, see [how to assign roles](how-to-assign-roles). For more on autoscale settings from Azure Monitor, see [Microsoft.Insights autoscalesettings](https://learn.microsoft.com/azure/templates/microsoft.insights/autoscalesettings).
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* To use autoscale, the role `microsoft.insights/autoscalesettings/write` must be assigned to the identity that manages autoscale. You can use any built-in or custom roles that allow this action. For general guidance on managing roles for Azure Machine Learning, see [Manage users and roles](/azure/machine-learning/how-to-assign-roles). For more on autoscale settings from Azure Monitor, see [Microsoft.Insights autoscalesettings](/azure/templates/microsoft.insights/autoscalesettings).
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## Define an autoscale profile
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