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Exam Overview
Exam Code AI-200
Exam Name Developing AI Cloud Solutions on Azure
Vendor Microsoft
Total Questions 56
Last Updated 26-Oct, 2026
Free AI-200 Questions Get Premium Access
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Free AI-200 Practice Questions

Explore 4 free practice questions for the Microsoft AI-200 exam and review the answers and explanations to support your preparation.

  1. Question 1

    Drag & Drop

    DRAG DROP You are designing a document ingestion pipeline for an AI application. Documents are uploaded by users and must be converted into searchable vector content. Arrange the steps in the correct order

    Show Answer & Explanation Hide Answer & Explanation

    Correct Answer


     A.    Store vectors and metadata in the search index
    B.    Generate embeddings for each chunk
    C.    Store the uploaded document in Azure Blob Storage
    D.    Split the extracted text into chunks

    Explanation


    The document must first be stored in a durable location such as Azure Blob Storage. After the content is available, the text can be extracted and split into smaller chunks. Embeddings are generated for each chunk so semantic similarity search can be performed. Finally, the vectors and metadata are stored in a vector-enabled index or database for retrieval during AI application execution.

  2. Question 2

    Single answer

    You are deploying a containerized Python AI application to Azure Container Apps. The application image is stored in Azure Container Registry. The deployment fails because the container app cannot pull the image. What should you configure?

    • Option A:
      A public DNS forwarding rule
      Correct
    • Option B:
      Registry access for the container app identity
      Correct
    • Option C:
      A storage lifecycle policy
      Correct
    • Option D:
      A Log Analytics query
      Correct
    Show Answer & Explanation Hide Answer & Explanation

    Correct Answer: B

    Explanation

    When Azure Container Apps pulls an image from Azure Container Registry, it needs permission to access the registry. This can be done by configuring registry credentials or using a managed identity with the appropriate pull permission. Without image pull access, the container app cannot download the image and the deployment fails.

  3. Question 3

    Drag & Drop

    You are designing an AI cloud solution that uses Azure SDKs. Match each requirement to the best practice

    Show Answer & Explanation Hide Answer & Explanation

    Correct Answer

    A.    Avoid hardcoded secrets — Use managed identity or Key Vault
    B.    Handle temporary service failures — Use retries with backoff
    C.    Improve SDK efficiency — Reuse client objects
    D.    Troubleshoot failures — Use structured logging and telemetry

    Explanation

    Modern Azure SDK development follows several important best practices for security, reliability, and
    performance. Applications should avoid storing credentials directly in code and instead use managed identities or Azure Key Vault for secure secret management. Temporary network or service interruptions are common in distributed cloud environments, so retry policies with exponential backoff help applications recover automatically from transient failures. Reusing SDK client objects improves connection management, reduces resource consumption, and increases overall application efficiency. Structured logging and telemetry provide visibility into application behavior, making it easier to diagnose failures, monitor performance, and troubleshoot issues across multiple Azure services and distributed AI workloads.

  4. Question 4

    Multiple answers

    You are developing an AI cloud solution on Azure. The solution includes a Python API that receives user requests and sends long-running AI jobs to a background processor. You need to ensure that the API responds quickly and that failed jobs can be retried. Which Azure service should you use between the API and the worker? 

    • Option A:
      Azure Container Registry
      Correct
    • Option B:
      Azure Cost Management
      Correct
    • Option C:
      Azure Service Bus Queue
      Correct
    • Option D:
      Azure Private DNS Zone
      Correct
    Show Answer & Explanation Hide Answer & Explanation

    Correct Answer: A, B, C, D

    Explanation

    Azure Service Bus Queue is suitable when an application needs reliable asynchronous communication between components. The API can place a job message on the queue and return a response to the user immediately. The worker can process messages independently and retry failed jobs if needed. This design improves reliability and prevents long-running AI tasks from blocking the user-facing API.