Question

Your team runs an Azure AI Foundry project that serves a chat application. The current production deployment uses version 3 of a foundation model on a serverless API endpoint. A newer version 4 has been released, and stakeholders want to validate its response quality against version 3 using the same evaluation dataset before committing to a full cutover, while keeping production traffic entirely on version 3. What is the most appropriate approach?

Accepted Answer

Create a separate deployment for version 4 under the same project and route evaluation traffic to it, leaving the version 3 deployment serving all production requests.

Answer

Update the existing version 3 deployment in place to point to version 4, then roll back if the evaluation results are unsatisfactory.

Answer

Delete the version 3 deployment and create a new deployment for version 4, since only one model version can exist per project.

Answer

Provision reserved provisioned throughput units for version 4 to guarantee that production traffic is unaffected during evaluation.