Microsoft Azure AI Engineer Associate AI-102 Practice Question
You have a Conversational language understanding project named SupportBot that is already deployed to production with the deployment name "prod". After adding new labeled utterances, you retrain the model. QA engineers must run tests against the new model while customers continue to use the existing model. Which action should you take?
Create a new deployment that references the retrained model and give its endpoint to the QA engineers.
Enable evaluation mode in Language Studio so that 10% of production traffic is automatically routed to the new model.
Publish the retrained model to the existing "prod" deployment and roll back if tests fail.
Export the project and import it into a separate Azure AI Language resource in the same region for testers to use.
Conversational language understanding allows multiple deployments of the same project. To make a new model available only to testers, create an additional deployment (for example, "test") that points to the newly trained model and share its prediction endpoint key and URL with the QA team. Keeping the original "prod" deployment unchanged ensures that customer traffic continues to use the previous model. Overwriting the "prod" deployment or exporting and recreating a new resource would interrupt production traffic, and the service has no built-in traffic-splitting feature that routes only a portion of requests to a new model.
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Microsoft Azure AI Engineer Associate AI-102
Implement natural language processing solutions
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