AI-200 Exam Question 31

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
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You are preparing a production deployment for an Azure Function app. The app will run across multiple environments.
The solution must support environment-specific configuration and prevent secrets from being stored in source control.
You need to develop the solution.
Solution: Use App Configuration with Key Vault references to store environment-specific settings and secrets, accessed from the function app by using a managed identity.
Does the solution meet the goal?
  • AI-200 Exam Question 32

    You must ensure that PII (personally identifiable information) such as names and phone numbers is automatically redacted from support ticket transcripts before they are stored. What should you use?
  • AI-200 Exam Question 33

    You are developing an Azure Function that calls external APIs by providing an access token for the API. The access token is stored in a secret named token in an Azure Key Vault named mykeyvault. You need to ensure the Azure Function can access the token. Which value should you store in the Azure Functions app configuration?
  • AI-200 Exam Question 34

    You deploy an AI application across multiple Azure regions.
    The application must be able to view writes across all regions within a predictable time window.
    You need to determine the appropriate consistency level.
    What are two consistency levels you can use to achieve the goal? Each correct answer presents a complete solution.
    NOTE: Each correct selection is worth one point.
  • AI-200 Exam Question 35

    Hotspot Question
    You are developing a Retrieval-Augmented Generation (RAG) solution for a company.
    AI responses and embedding vectors are cached in Redis.
    The solution must meet the following requirements:
    - AI responses must expire exactly 24 hours after they are cached.
    - Cached embeddings must always reflect the current source data.
    You need to configure Redis to meet the requirements.
    NOTE: Each correct selection is worth one point.