Azure for Students - errors when trying to deploy a model

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Azure for Students - errors when trying to deploy a model

funguy 0

Hi,

I have the Azure student subscription and figured out (thanks to the additional comments in this post: https://learn.microsoft.com/en-us/answers/questions/5535918/azure-student-subscription-region-error) my list of available regions to create a project: ["austriaeast","malaysiawest","norwayeast","switzerlandnorth","brazilsouth"]

However, when trying to deploy a model in Azure AI Foundry, I can only select "East US 2" or "Sweden Central" as the resource location, since I apparently have no quota for the other locations. When then trying to deploy the model, I get the following error:

{ "error": { "code": "InvalidTemplateDeployment", "message": "The template deployment failed with multiple errors. Please see details for more information.", "details": [ { "code": "RequestDisallowedByAzure", "message": "Resource 'ads-mf11jf7k-swedencentral' was disallowed by Azure: This policy maintains a set of best available regions where your subscription can deploy resources. The objective of this policy is to ensure that your subscription has full access to Azure services with optimal performance. Should you need additional or different regions, contact support..", "target": "ads-mf11jf7k-swedencentral" }, { "code": "RequestDisallowedByAzure", "message": "Resource 'ads-mf11jf7k-swedencentral_project' was disallowed by Azure: This policy maintains a set of best available regions where your subscription can deploy resources. The objective of this policy is to ensure that your subscription has full access to Azure services with optimal performance. Should you need additional or different regions, contact support..", "target": "ads-mf11jf7k-swedencentral_project" } ] } }

However, I can't select one of the options I was assigned when trying to deploy a model. What can I do?

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Answer 1

Anonymous

Hi funguy,

Thanks for Posting your Question in Microsoft Q&A Portal

The issue arises because Azure for Students subscriptions have strict region restrictions applied via Azure policies. Your subscription has a limited set of allowed regions ["austriaeast","malaysiawest","norwayeast","switzerlandnorth","brazilsouth"] for resource deployment, but Azure AI Foundry service itself is only available in specific regions like "East US 2" or "Sweden Central," which you do not have quota access to under your student subscription policies. This mismatch leads to the deployment error stating the resource location is disallowed by Azure policies.

Recommended solution to resolve the issue:

Check your allowed deployment regions in Azure Policy assignments as mentioned 5535918 post to confirm where you can deploy resources.Since Azure AI Foundry is only available in limited regions not allowed in your student subscription, consider these options:

Request a quota increase or access for the relevant AI Foundry regions via Azure support

Refer document to raise request:

https://learn.microsoft.com/en-us/troubleshoot/azure/general/region-access-request-process

Resolve location ineligible errors - Azure Resource Manager | Microsoft Learn

Use a different Azure subscription type such as Pay-As-You-Go or other standard subscriptions without region restrictions.

For more detailed steps on requesting quota increase and managing Azure AI Foundry quotas, refer to https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/quota?pivots=fdp-project

Quota increase requests can be submitted via the quota increase request form. Due to high demand, quota increase requests are accepted and filled in the order they're received. Priority is given to customers who generate traffic that consumes the existing quota allocation. Your request might be denied if this condition isn't met.

You can submit a service request for other rate limits.

for more details you can refer https://learn.microsoft.com/en-us/azure/ai-foundry/openai/quotas-limits?tabs=REST

I hope the provided details help. Please let me know if you have any further questions. if the provided answer is helpful, please accept as Yes and upvote so that it can help others in the community.

funguy 0 Reputation points

2025-09-02T07:17:14.8566667+00:00

Hi Sandhya,

thanks for your reply! Could you provide more info on the "pay-as-you-go"-option?

For my use case, I just need to be able to prompt the models from within my python code, so I don't need to deploy it in the traditional sense that other people can also use it. Can I also use the 100$ that I received in the student subscription for the pay-as-you-go option? If so, how?

Thanks in advance!
Anonymous

2025-09-02T07:34:44.9733333+00:00
funguy, Thank you for your reply!

The Pay-As-You-Go (PAYG) option is a standard Azure subscription where you pay only for the resources you use, without the limitations that student subscriptions have. This gives you full access to all regions and services, including Azure AI Foundry, which should allow you to deploy and prompt models directly from your Python code.

Key points regarding the Pay-As-You-Go option related to your student subscription and use case:

You cannot directly use the $100 credit granted in the Azure for Students subscription for the Pay-As-You-Go plan because they are different subscription types. However, after exhausting your student credit or if you want to lift the region and quota restrictions, you can upgrade your Azure for Students subscription to a Pay-As-You-Go subscription.

Upgrading to Pay-As-You-Go means you will pay for resources you consume beyond any free tier limits, but you will no longer be limited by the student subscription policies such as region restrictions. This allows you to deploy or run Azure AI Foundry models from any supported region.

For your use case prompting models from Python code, you don't need to deploy the model for public use; you just need the right subscription type and region access to provision the service. Pay-As-You-Go will give you this flexibility

To upgrade to PAYG pay-as-you-go rates

Go to the Azure Portal.

Find the option to upgrade your Azure for Students subscription to Pay-As-You-Go.

Information on Pay-As-You-Go subscription, pricing, and upgrade path: https://azure.microsoft.com/en-us/pricing/purchase-options/azure-account

Note that once upgraded, you lose access to the initial $100 credit tied to the student offer, but you gain access to all supported regions and higher quotas.

You will need a valid payment method like a credit or debit card associated with the Pay-As-You-Go subscription.

If you want to retain free credits under student subscription, you have to stay in that plan, but you will be limited to restricted regions and quotas as you have experienced.

This approach will allow you to use Azure AI Foundry from your Python code without region restrictions and without needing to deploy models for broader access.

For more details on upgrading student PAYG and subscription types refer below document: https://learn.microsoft.com/en-us/azure/cost-management-billing/manage/upgrade-azure-subscription

Do let me know if you have any further questions
funguy 0 Reputation points

2025-09-02T07:49:21.2966667+00:00

Hi Sandhya, thanks for the reply!

The pay-as-you-go option is then unfortunately not feasible for me, as I have limited budget (I'm a student, after all)...

From your experience, do I have a chance that my eligible regions might be adjusted so that I can deploy models via AI Foundry? Or should I look for alternatives outside of Azure?
Anonymous

2025-09-02T08:26:51.79+00:00
Hi funguy, thanks for the follow-up!

The chances of adjusting your eligible regions in an Azure for Students subscription to deploy Azure AI Foundry models are quite limited because region restrictions are enforced by policy and tied to student subscription safeguards.

here are the key points about the situation and possible next steps:

Azure region restrictions for student subscriptions are mostly fixed for governance and cost control reasons, so changing them is generally not possible by the user. These policies control where supported services can be deployed to optimize performance and manage resources.

You can try to request a quota as (I mentioned in my 1st response) increase or region access through Azure support by raising a support ticket in the Azure Portal explaining your educational use case. However, such requests often get declined for student subscriptions due to inherent subscription restrictions.

If your goal is AI/ML experimentation, consider alternative Azure services supported in your allowed regions like Azure AI Studio or Azure Machine Learning Studio that might not have the same region restrictions as Azure AI Foundry.

yes, you can alternatively explore free or low-cost AI cloud services outside of Azure that fit your budget and regional availability.
Anonymous

2025-09-03T08:35:23.92+00:00

Hi funguy, following up to see if you have a chance to check my previous response and helped, do let me know if you have any further questions on this.
nathan crowder 0 Reputation points

2025-12-20T00:29:12.56+00:00

@Anonymous I'm trying to do the same with deploying a model that was used for forecasting. I used multiple attempts for selecting minimal VM setups for both the instance and cluster types for training, but when I try to deploy it fails, but generates no log at all to see what the issue is. I'm in the US and do everything using East US2.
Anonymous

2025-12-22T02:45:10.7466667+00:00

Hello nathan crowder**,** As I suggested before, please submit a Request on quota increase or access for the relevant AI Foundry regions via Azure support

Refer document to raise request:

https://learn.microsoft.com/en-us/troubleshoot/azure/general/region-access-request-process

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Azure for Students - errors when trying to deploy a model

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