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Microsoft Developing AI Cloud Solutions on Azure : AI-200
- Exam Code: AI-200
- Exam Name: Developing AI Cloud Solutions on Azure
- Updated: Sep 17, 2026
- Q & A: 144 Questions and Answers
About Microsoft AI-200 Exam Questions
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Microsoft AI-200 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Implement Azure AI solutions | - Implement knowledge mining with Azure AI Search - Implement natural language processing solutions - Implement computer vision solutions - Implement generative AI solutions using Azure OpenAI |
| Implement and monitor AI workloads | - Monitor performance and troubleshoot issues - Deploy AI models and services |
| Plan and manage Azure AI solutions | - Plan security and compliance requirements - Monitor and optimize AI solutions - Select appropriate Azure AI services |
Microsoft Developing AI Cloud Solutions on Azure Sample Questions:
Question #1
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.
You are using Azure Monitor Application Insights to investigate a production API. You open the Logs blade and set the time range to Last 24 hours.
An engineer recommends the following query to count requests by result code and sort the results from most frequent to least frequent:
requests
| summarize request_count = count() by resultCode
| order by request_count desc
You need to determine whether the query returns the number of requests grouped by result code and sorted from most to least frequent.
Solution: The query lists every individual request along with its result code.
Does the solution meet the goal?
- A. Yes
- B. No
Correct Answer: B 🗳️
Explanation: Only visible for BraindumpsPrep members. You can sign-up / login (it's free).
Question #2
You need to address the known issue resulting from vector similarity queries.
Which two actions should you perform? Each correct answer presents part of the solution. Choose two.
NOTE: Each correct selection is worth one point.
- A. Add a composite index on the vector fields and metadata properties of the container.
- B. Reduce the numeric precision of the vector embeddings where supported.
- C. Change the vector index type from flat to quantizedFlat or diskANN.
- D. Set the account consistency level to Strong.
Correct Answer: B,C 🗳️
Explanation: Only visible for BraindumpsPrep members. You can sign-up / login (it's free).
Question #3
You have an existing AKS cluster and a container image stored in Azure Container Registry.
You must deploy a new version by using a Deployment manifest that supports rolling updates without interrupting traffic.
You need to perform a rolling update by using a manifest file.
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.
Correct Answer:
Explanation:
Question #4
You plan to deploy an Azure Container Apps app named App1. App1 will use an access key to connect to a backend API.
The solution must store the key outside of the App1 environment and minimize maintenance efforts.
You need to configure secure key storage for App1.
Which configurations should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
* Provide the key storage for App1: Azure Key Vault secret
* Secure App1 access to the key storage: Managed identity
An API access key is a sensitive string value, so it should be stored as an Azure Key Vault secret , not as an Azure Key Vault cryptographic key. Azure Container Apps supports direct Key Vault secret references , allowing sensitive values to remain centrally stored outside the container app rather than being embedded in images or supplied directly as Container Apps secret values. Microsoft recommends Key Vault references for production secrets because they provide centralized lifecycle management and avoid placing secret values directly in application configuration.
App1 should authenticate to Key Vault by using a managed identity . Azure Container Apps supports both system-assigned and user-assigned managed identities, enabling the workload to obtain Microsoft Entra tokens without maintaining client secrets or credentials. The identity must be granted appropriate Key Vault permissions, such as the Key Vault Secrets User RBAC role, to retrieve the stored secret.
This configuration also minimizes maintenance. When the Key Vault reference omits a specific secret version, Container Apps uses the latest version and automatically detects newer versions, retrieving the updated value within approximately 30 minutes.
Therefore, the required combination is Azure Key Vault secret + Managed identity .
Study Guide references: Azure Container Apps # secrets management; Key Vault references; managed identities; secret rotation and runtime retrieval.
Question #5
You plan to deploy a container to an Azure App Service API app named api1. You host the source code for api1 in a GitHub repository. The container uses the API key at runtime to connect to a backend service.
The container must be able to retrieve the API key at runtime without exposing it in the source repository or Git commit history. The API key must not be stored in application configuration directly. The API key must be accessed securely from Azure Key Vault.
You need to ensure that the API key is stored securely in Azure Key Vault and is available to the container at runtime without being exposed in source control or Git commit history.
Solution: Store the API key as an App Service application setting configured through the Azure Portal.
Does the solution meet the goal?
- A. Yes
- B. No
Correct Answer: B 🗳️
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