Manage and increase quotas for resources with Azure AI Studio

Article
02/06/2024

Note

Azure AI Studio is currently in public preview. This preview is provided without a service-level agreement, and we don't recommend it for production workloads. Certain features might not be supported or might have constrained capabilities. For more information, see Supplemental Terms of Use for Microsoft Azure Previews.

Quota provides the flexibility to actively manage the allocation of rate limits across the deployments within your subscription. This article walks through the process of managing quota for your Azure AI Studio virtual machines and Azure OpenAI models.

Azure uses limits and quotas to prevent budget overruns due to fraud, and to honor Azure capacity constraints. It's also a good way to control costs for admins. Consider these limits as you scale for production workloads.

In this article, you learn about:

Default limits on Azure resources
Creating Azure AI hub resource-level quotas.
Viewing your quotas and limits
Requesting quota and limit increases

Special considerations

Quotas are applied to each subscription in your account. If you have multiple subscriptions, you must request a quota increase for each subscription.

A quota is a credit limit on Azure resources, not a capacity guarantee. If you have large-scale capacity needs, contact Azure support to increase your quota.

Note

Azure AI Studio compute has a separate quota from the core compute quota.

Default limits vary by offer category type, such as free trial, pay-as-you-go, and virtual machine (VM) series (such as Dv2, F, and G).

Azure AI Studio quota

The following actions in Azure AI Studio consume quota:

Creating a compute instance.
Building a vector index.
Deploying open models from model catalog.

Azure AI Studio compute

Azure AI Studio compute has a default quota limit on both the number of cores and the number of unique compute resources that are allowed per region in a subscription.

The quota on the number of cores is split by each VM Family and cumulative total cores.
The quota on the number of unique compute resources per region is separate from the VM core quota, as it applies only to the managed compute resources

To raise the limits for compute, you can request a quota increase in the Azure AI Studio.

Available resources include:

Dedicated cores per region have a default limit of 24 to 300, depending on your subscription offer type. You can increase the number of dedicated cores per subscription for each VM family. Specialized VM families like NCv2, NCv3, or ND series start with a default of zero cores. GPUs also default to zero cores.
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 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.

When opening the support request to increase the total compute limit, provide the following information:

Select Technical for the issue type.
Select the subscription that you want to increase the quota for.
Select Machine Learning as the service type.
Select the resource that you want to increase the quota for.
In the Summary field, enter "Increase total compute limits"
Select Compute instance the problem type and Quota as the problem subtype.
Select Next.
On the Additional details page, provide the subscription ID, region, new limit (between 500 and 2500) and business justification to increase the total compute limits for the region.
Select Create to submit the support request ticket.

Azure AI Studio shared quota

Azure AI Studio provides a pool of shared quota that is available for different users across various regions to use concurrently. Depending upon availability, users can temporarily access quota from the shared pool, and use the quota to perform testing for a limited amount of time. The specific time duration depends on the use case. By temporarily using quota from the quota pool, you no longer need to file a support ticket for a short-term quota increase or wait for your quota request to be approved before you can proceed with your workload.

Use of the shared quota pool is available for testing inferencing for Llama-2, Phi, Nemotron, Mistral, Dolly and Deci-DeciLM models from the Model Catalog. You should use the shared quota only for creating temporary test endpoints, not production endpoints. For endpoints in production, you should request dedicated quota. Billing for shared quota is usage-based, just like billing for dedicated virtual machine families.

Container Instances

For more information, see Container Instances limits.

Storage

Azure Storage has a limit of 250 storage accounts per region, per subscription. This limit includes both Standard and Premium storage accounts

View and request quotas in Azure AI Studio

Use quotas to manage compute target allocation between multiple Azure AI hub resources in the same subscription.

By default, all Azure AI hub resources share the same quota as the subscription-level quota for VM families. However, you can set a maximum quota for individual VM families for more granular cost control and governance on Azure AI hub resources in a subscription. Quotas for individual VM families let you share capacity and avoid resource contention issues.

In Azure AI Studio, select Manage from the top menu. Select Quota to view your quota at the subscription level in a region for both Azure Machine Learning virtual machine families and for your Azure OpenAI resources.

To request more quota, select the Request quota button for subscription and region.

Share via