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Update how-to-manage-quotas.md
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articles/machine-learning/how-to-manage-quotas.md

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+ **Low-priority cores per region** have a default limit of 100 to 3,000, depending on your subscription offer type. The number of low-priority cores per subscription can be increased and is a single value across VM families.
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+ **Total compute limit per region** has a default limit of 500 per region within a given subscription and can be increased up to a maximum value of 2500 per region. This limit is shared between training clusters, compute instances, and managed online endpoint deployments. A compute instance is considered a single-node cluster for quota purposes. In order to increase the total compute limit, [open an online customer support request](https://ms.portal.azure.com/#view/Microsoft_Azure_Support/NewSupportRequestV3Blade/callerWorkflowId/5088c408-f627-4398-9aa3-c41cdd93a6eb/callerName/Microsoft_Azure_Support%2FHelpAndSupportOverview.ReactView). Provide the following information:
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1. When opening the support request, select __Technical__ as the __Issue type__.
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1. Select the subscription of your choice
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1. Select __Machine Learning__ as the __Service__.
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1. Select the resource of your choice
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1. In the summary, mention "Increase total compute limits"
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1. Select __Compute Cluster__ as the __Problem type__ and __Cluster does not scale up or is stuck in resizing__ as the __Problem subtype__.
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:::image type="content" source="media/how-to-manage-quotas/problem-description.png" alt-text="Screenshot of the problem description tab.":::
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1. On the __Additional details__ tab, provide the subscription ID, region, new limit (between 500 and 2500) and business justification if you would like to increase the total compute limits in this region.
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:::image type="content" source="media/how-to-manage-quotas/additional-details.png" alt-text="Screenshot of the additional details tab.":::
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1. Finally, select __Create__ to create a support request ticket.
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+ **Total compute limit per region** has a default limit of 500 per region within a given subscription and can be increased up to a maximum value of 2500 per region. This limit is shared between training clusters, compute instances, and managed online endpoint deployments. A compute instance is considered a single-node cluster for quota purposes.
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The following table shows more limits in the platform. Reach out to the Azure Machine Learning product team through a **technical** support ticket to request an exception.
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> [!NOTE]
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> This endpoint limit increase request is different from VM quota increase request. If your request is related to VM quota increase, follow the instructions in the [VM quota increases](#vm-quota-increases) section.
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### Compute limit increases
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In order to increase the total compute limit, [open an online customer support request](https://ms.portal.azure.com/#view/Microsoft_Azure_Support/NewSupportRequestV3Blade/callerWorkflowId/5088c408-f627-4398-9aa3-c41cdd93a6eb/callerName/Microsoft_Azure_Support%2FHelpAndSupportOverview.ReactView). Provide the following information:
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1. When opening the support request, select __Technical__ as the __Issue type__.
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1. Select the subscription of your choice
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1. Select __Machine Learning__ as the __Service__.
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1. Select the resource of your choice
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1. In the summary, mention "Increase total compute limits"
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1. Select __Compute Cluster__ as the __Problem type__ and __Cluster does not scale up or is stuck in resizing__ as the __Problem subtype__.
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:::image type="content" source="media/how-to-manage-quotas/problem-description.png" alt-text="Screenshot of the problem description tab.":::
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1. On the __Additional details__ tab, provide the subscription ID, region, new limit (between 500 and 2500) and business justification if you would like to increase the total compute limits in this region.
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:::image type="content" source="media/how-to-manage-quotas/additional-details.png" alt-text="Screenshot of the additional details tab.":::
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1. Finally, select __Create__ to create a support request ticket.
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## Next steps
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+ [Plan and manage costs for Azure Machine Learning](concept-plan-manage-cost.md)

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