Azure foundry deployment returns empty Target URI

Question

I am trying to deploy gpt-5-pro model, the wizard goes through, but the deployment model does not return any target URI (it is left as empty)

Answer 1

Hi Ali Mahmoudzadeh,

This usually happens when the deployment is created successfully, but the backend endpoint has not finished getting ready yet.

In Azure AI Foundry, the deployment wizard can complete before the service endpoint is fully provisioned. When that happens, the Target URI field shows up as empty even though the deployment looks successful. This is a timing and readiness issue, not a problem with your configuration.

Here are a few things you can check.

First, give the deployment some time and refresh the page. Right after deployment, the endpoint may not be available immediately. Waiting a few minutes and refreshing the deployment details often makes the Target URI appear once the backend finishes provisioning. This behavior has been seen with other Foundry and Azure OpenAI deployments as well.

Second, make sure the deployment state is healthy. Open the deployment in Azure AI Foundry and confirm that the deployment status is completed and not still initializing. If the deployment is still in progress, the Target URI will remain empty until the process finishes.

Third, confirm the region supports the selected model. Some models are available only in specific regions. If the model is not fully supported in the selected region, the deployment can appear successful but fail to expose an endpoint. Checking model and region availability helps avoid this mismatch.

Fourth, check the project endpoint instead of the deployment view. Even when the Target URI is not shown in the deployment screen, the project endpoint can still be valid. You can find the project endpoint on the project overview page in Foundry, and it can be used together with the deployment name for API calls.

In short: an empty Target URI usually means the endpoint is still being prepared or not yet surfaced in the UI. Refreshing after some time, verifying deployment status, and confirming region support typically resolves the issue without changing anything in your setup.

Reference docs:

• Troubleshooting Deployment Issues in Azure OpenAI Studio: https://learn.microsoft.com/azure/ai-foundry/openai/quotas-limits?tabs=REST#how-to-request-quota-increases
• Create and deploy an Azure OpenAI in Azure AI Foundry Models resource (CLI): https://learn.microsoft.com/azure/ai-foundry/openai/how-to/create-resource
• https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/models

Do let me know if you have any further queries.

Thankyou!