Merge pull request #270104 from dem108/patch-27

Clarify on extra quota on managed online endpoint

Author: prmerger-automator[bot]

articles/machine-learning/how-to-deploy-online-endpoints.md

@@ -71,9 +71,7 @@ Before following the steps in this article, make sure you have the following pre
 
 ### Virtual machine quota allocation for deployment
 
-For managed online endpoints, Azure Machine Learning reserves 20% of your compute resources for performing upgrades on some VM SKUs. If you request a given number of instances in a deployment, you must have a quota for `ceil(1.2 * number of instances requested for deployment) * number of cores for the VM SKU` available to avoid getting an error. For example, if you request 10 instances of a [Standard_DS3_v2](/azure/virtual-machines/dv2-dsv2-series) VM (that comes with 4 cores) in a deployment, you should have a quota for 48 cores (`12 instances * 4 cores`) available. To view your usage and request quota increases, see [View your usage and quotas in the Azure portal](how-to-manage-quotas.md#view-your-usage-and-quotas-in-the-azure-portal).
-
-There are certain VM SKUs that are exempted from extra quota reservation. To view the full list, see [Managed online endpoints SKU list](reference-managed-online-endpoints-vm-sku-list.md).
+For managed online endpoints, Azure Machine Learning reserves 20% of your compute resources for performing upgrades on some VM SKUs. If you request a given number of instances for those VM SKUs in a deployment, you must have a quota for `ceil(1.2 * number of instances requested for deployment) * number of cores for the VM SKU` available to avoid getting an error. For example, if you request 10 instances of a [Standard_DS3_v2](/azure/virtual-machines/dv2-dsv2-series) VM (that comes with 4 cores) in a deployment, you should have a quota for 48 cores (`12 instances * 4 cores`) available. This extra quota is reserved for system-initated operations such as OS upgrade, VM recovery etc, and it won't incur cost unless such operation runs. To view your usage and request quota increases, see [View your usage and quotas in the Azure portal](how-to-manage-quotas.md#view-your-usage-and-quotas-in-the-azure-portal). To view your cost of running managed online endpoints, see [View cost for managed online endpoint](how-to-view-online-endpoints-costs.md). There are certain VM SKUs that are exempted from extra quota reservation. To view the full list, see [Managed online endpoints SKU list](reference-managed-online-endpoints-vm-sku-list.md).
 
 Azure Machine Learning provides a [shared quota](how-to-manage-quotas.md#azure-machine-learning-shared-quota) pool from which all users can access quota to perform testing for a limited time. When you use the studio to deploy Llama-2, Phi, Nemotron, Mistral, Dolly and Deci-DeciLM models from the model catalog to a managed online endpoint, Azure Machine Learning allows you to access this shared quota for a short time.