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Microsoft

AI-102 · Question #294

Drag and Drop Question You have an app that manages feedback. You need to ensure that the app can detect negative comments by using the Sentiment Analysis API in Azure AI Language. The solution must…

The correct answer is Deploy a Docker container to an on-premises server.; Provision the Language service resource in Azure.; Run the container and query the prediction endpoint. The correct sequence ensures that managed feedback stays on the company's internal network by using Azure AI Language containers on-premises. First, you provision the Language service resource in Azure to obtain the required API key and billing endpoint. Then, you deploy the…

Submitted by daniela_cl· Mar 30, 2026Plan and manage an Azure AI solution - specifically deploying Azure AI Language containers for on-premises or network-restricted environments to satisfy data residency and privacy requirements.

Question

Drag and Drop Question You have an app that manages feedback. You need to ensure that the app can detect negative comments by using the Sentiment Analysis API in Azure AI Language. The solution must ensure that the managed feedback remains on your company's internal network. Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order. NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select. Answer:

Exhibit

AI-102 question #294 exhibit

Answer Area

Drag items

Identify the Language service endpoint URL and query the prediction endpoint.Provision the Language service resource in Azure.Run the container and query the prediction endpoint.Deploy a Docker container to an on-premises server.Deploy a Docker container to an Azure container instance.

Correct arrangement

  • Deploy a Docker container to an on-premises server.
  • Provision the Language service resource in Azure.
  • Run the container and query the prediction endpoint.

Explanation

The correct sequence ensures that managed feedback stays on the company's internal network by using Azure AI Language containers on-premises. First, you provision the Language service resource in Azure to obtain the required API key and billing endpoint. Then, you deploy the Docker container (which contains the Sentiment Analysis model) to an on-premises server to keep data within the internal network. Finally, you run the container and query the prediction endpoint locally, ensuring no feedback data leaves the corporate network.

Topics

#Azure AI Language#Sentiment Analysis#Containerized AI Services#On-Premises Deployment

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