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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 14, 2026
- Q & A: 144 Questions and Answers
About Microsoft Developing AI Cloud Solutions on Azure : AI-200 Exam
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Microsoft AI-200 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Implement Azure AI solutions | - Implement natural language processing solutions - Implement generative AI solutions using Azure OpenAI - Implement computer vision solutions - Implement knowledge mining with Azure AI Search |
| Implement and monitor AI workloads | - Deploy AI models and services - Monitor performance and troubleshoot issues |
| Plan and manage Azure AI solutions | - Plan security and compliance requirements - Select appropriate Azure AI services - Monitor and optimize AI solutions |
Microsoft Developing AI Cloud Solutions on Azure Sample Questions:
Question #1
You need to troubleshoot connectivity failures between microservices running in AKS.
Which troubleshooting actions should you perform? To answer, move the appropriate action to the correct troubleshooting scenario. You may use each action once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
* Service fails to communicate with another service: Inspect Kubernetes service endpoints.
* Pod restarts repeatedly: Inspect container logs.
* Readiness probe failures are observed: Inspect Pod descriptions.
For a service-to-service communication failure , first inspect the Kubernetes service endpoints . Microsoft' s AKS troubleshooting guidance recommends verifying that the destination pod IP address and application port appear as endpoints for the Kubernetes Service. An empty or incorrect endpoint list commonly indicates a selector/label mismatch, incorrect port configuration, or unavailable backend pods.
For a pod that restarts repeatedly , inspect the container logs , including the previous container instance when necessary. Microsoft specifically recommends kubectl logs < pod > --previous for workloads that repeatedly restart because it exposes application errors and termination messages from the container immediately before the restart.
For readiness probe failures , inspect the Pod description by using kubectl describe pod. The description exposes the configured health probes, pod conditions, container state, and associated probe-failure events, allowing you to determine whether the probe path, port, timing, or application readiness behavior is incorrect.
Microsoft recommends reviewing kubectl describe output when pods are not Ready or health probes are failing.
Therefore, the correct mapping is service endpoints # container logs # Pod descriptions .
Study Guide references: AKS troubleshooting; Kubernetes Services and endpoints; container logging; Pod health; readiness/liveness probes; kubectl describe and kubectl logs.
Question #2
You need to deploy Azure function resources and apps by using an automated, version-controlled CI/CD pipeline that supports declarative infrastructure deployment. What should you use?
- A. Local Git deployment
- B. Azure CLI
- C. Azure Functions Core Tools
- D. GitHub Actions
Correct Answer: D 🗳️
Question #3
You are implementing an application by using Azure Event Grid to push near-real-time information to customers.
You have the following requirements:
* You must send events to thousands of customers that include hundreds of various event types.
* The events must be filtered by event type before processing.
* Authentication and authorization must be handled by using Microsoft Entra ID.
* The events must be published to a single endpoint
You need to implement Azure Event Grid
Solution: Publish events to a partner topic. Create an event subscription for each customer.
Does the solution meet the goal?
- A. Yes
- B. No
Correct Answer: B 🗳️
Explanation: Only visible for Free4Torrent members. You can sign-up / login (it's free).
Question #4
You are troubleshooting a production Azure OpenAI service that is experiencing intermittent connectivity issues. All telemetry is sent to a Log Analytics workspace.
You must write a KQL query that analyzes the AppRequests table. The query must filter for requests that occurred within the last 30 minutes and have a failed status.
The final output must display the total number of failures for each unique operation.
You need to select the KQL operators required to filter the time range and aggregate the failure counts.
Which two operators should you use? Each correct answer presents part of the solution. Choose two.
NOTE: Each correct selection is worth one point.
- A. where
- B. summarize
- C. project
- D. distinct
Correct Answer: A,B 🗳️
Question #5
You plan to develop an Azure Functions app with an HTTP trigger.
The app must support the following functionality:
Event-driven scaling -
Ability to use custom Linux images for function execution
You need to identify the app ' s hosting plan and the maximum amount of time that the app function can take to respond to incoming requests.
Which configuration setting values should you use? To answer, select the appropriate values in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
* Hosting plan: Premium
* Timeout value: 230 seconds
The correct hosting option is the Azure Functions Premium plan . Microsoft documents that the Premium plan supports event-driven scaling , where Azure Functions dynamically adds or removes host instances based on incoming trigger activity. It also supports Linux container deployments , which is required when the function app must execute from a custom Linux container image. A Dedicated App Service plan can host Linux containers, but it does not provide native Functions event-driven scaling. The legacy Consumption plan supports event-driven scaling but does not satisfy the custom Linux container requirement in this question.
For an HTTP-triggered function , the maximum time available to return an HTTP response is 230 seconds .
This limit applies even though a Premium-plan function can have a much longer or effectively unbounded execution timeout. Microsoft explains that the 230-second response limit results from the Azure Load Balancer ' s default idle timeout. If processing continues beyond this point, the function can continue executing, but the client will receive a timeout and the function cannot return its eventual response over that original HTTP connection.
Therefore, Premium + 230 seconds is the required combination.
Study Guide references: Azure Functions hosting options; Premium plan; Linux container support; event- driven scaling; HTTP-trigger timeout behavior.
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