Error 715-123420 when deploying any model in Microsoft Foundry

Hello @保元 駿

Based on what you've already tested, this does not look like a model, region, quota, or Foundry-resource configuration issue. You reproduced the same 715-123420 error across different resources, regions, and models.

Microsoft moderators have confirmed in several recent Q&A cases that 715-123420 is associated with a service-side fraud/risk protection hold and requires review by the appropriate Microsoft internal team. It isn't normally something that can be cleared by changing deployment settings.

I would not keep retrying deployments, recreating Foundry resources, or switching regions. Those steps generally don't remove this type of restriction and can make troubleshooting noisier.

Since Azure Support is directing you to a paid technical plan, I would ask a Microsoft Q&A moderator to assist with escalation/private-message collection for the backend review. Similar 715-123420 cases have been handled this way when the customer could not open the required support case directly.

You already have the right information ready:

• Subscription ID
• Foundry Resource ID
• Client Request ID
• Trace ID
• Service Request ID
• UTC timestamp of a failed deployment

Please don't post those identifiers publicly; provide them only through private message or a secure support channel.

At this point, the next useful action is backend review of the subscription/account risk flag, not additional deployment troubleshooting.

Please "Accept the Answer" if this information helped you. This will help us and others in the community as well.

Thank you for your response.

I will stop any further deployment attempts as recommended.

Azure Support informed me that I would need a paid technical support plan, so I am currently unable to open the required technical support case myself.

Could you please help escalate error 715-123420 to the appropriate Microsoft Foundry / Risk Protection backend team for review?

I have the following information ready:

• Subscription ID
• Foundry Resource ID
• Client Request ID
• Trace ID
• Service Request ID
• UTC timestamp of the failed deployment

I can provide these details via private message. Please let me know how I should proceed or send me a private message if possible.

Hello @保元 駿 ,

Welcome to Microsoft Q&A .Thank you for reaching out to us.

The current behavior suggests that the deployment request may be failing during an earlier validation stage before the model provisioning process begins. The error message itself does not expose the exact validation reason, so confirmation requires additional backend investigation.

Possible areas that may require review include:

• Subscription eligibility validation
• Subscription-level authorization checks
• Automated risk or trust validation controls
• Model deployment access validation

Regarding the request for an RTFP review, the available information does not conclusively confirm that an RTFP restriction is present. However, the observed pattern is consistent with scenarios where additional backend validation may be required to determine whether a subscription-level condition is preventing deployments from completing.

The following checks can help rule out common deployment blockers before backend investigation.

1. Confirming Model Availability Verify that the selected models are supported in the intended region and deployment type. Checks:
   • Confirm model availability for the selected Azure region.
   • Confirm that the selected deployment type (for example, Global Standard) is supported for the model.
2. Validating Quota and Capacity Availability Confirm that sufficient quota is available for:
   • Subscription
   • Region
   • Selected model deployment
   Quota or capacity issues normally return more specific quota-related messages. However, validating quota helps eliminate standard deployment limitations.
3. Verifying Resource Provider Registration Confirm that the required resource providers are registered and in a healthy state:

• Microsoft.CognitiveServices
  • Microsoft.MachineLearningServices Expected status: Registered

1. Reviewing Governance and Policy Restrictions Review Azure Policy assignments that may restrict:
   • AI model deployments
   • Allowed regions
   • Resource types
   • Deployment configurations
2. Performing Additional Deployment Validation To determine whether the issue is limited to a specific deployment method or occurs at the service level:
   • Retry after a short interval to rule out temporary service behavior.
   • Attempt a deployment with a new deployment name to exclude deployment-specific inconsistencies.
   • Test deployment through Azure AI Foundry portal.
   • If possible, test through Azure CLI or ARM/Bicep to confirm whether the failure occurs at the service layer.

As an additional verification , please note that

For sponsored subscriptions, it may also be useful to confirm that the selected models appear under the appropriate model collection in Azure AI Foundry, as model eligibility and billing behavior can vary depending on the model source.

The following references might be helpful , please check them out

• Region availability for Foundry Models sold by Azure - Microsoft Foundry | Microsoft Learn
• Azure OpenAI in Microsoft Foundry Models Quotas and Limits - Microsoft Foundry | Microsoft Learn
• Azure resource providers and types - Azure Resource Manager | Microsoft Learn
• Overview of Azure Policy - Azure Policy | Microsoft Learn
• az cognitiveservices account deployment | Microsoft Learn
• Sponsorship Coverage for Microsoft Foundry Models | Microsoft Learn

We have reached out to you on private messenger for further assistance

Thank you