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Microsoft AI-200 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Develop containerized AI solutions on Azure | 25% | - Monitor and troubleshoot containerized workloads
|
| Topic 2: Secure, monitor, and optimize AI solutions | 20% | - Implement observability and reliability
|
| Topic 3: Integrate backend services and build event-driven architectures | 25% | - Build serverless APIs and workflows
|
| Topic 4: Develop AI solutions using Azure data services | 30% | - Design and optimize data access and retrieval
|
Microsoft Developing AI Cloud Solutions on Azure Sample Questions:
You need to improve throughput for concurrent application requests to PostgreSQL.
What should you implement?
- A. Increase shared_buffers.
- B. Increase max_connections.
- C. Implement connection pooling.
- D. Enable read replicas.
Correct Answer: C 🗳️
Explanation: Only visible for ExamPrepAway members. You can sign-up / login (it's free).
You are building o back end pipeline that receives Al inference requests. The pipeline must perform the following actions:
* Publish a message so that multiple independent consumers receive it.
* Process massages in order through a single consumer entity.
* isolate any failed messages
You need to configure the appropriate Service Bus entities.
How should you configure the service bus entities? To answer, move the appropriate configurations to the correct requirements. You may use each configuration once..
Correct Answer:

Explanation:
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: Embed the API key as a hardcoded environment variable in the Dockerfile.
Does the solution meet the goal?
- A. Yes
- B. No
Correct Answer: B 🗳️
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 🗳️
You are investigating high latency in an AI search application that processes millions of requests daily.
Telemetry is stored in Azure Monitor Logs.
You must create a KQL query that correlates information from the AppRequests table and the AppDependencies table. The query must meet the following requirements:
* Include only data from the last 24 hours.
* Filter for failed requests only.
* Calculate the average duration of dependencies, grouped by operation.
The query must follow best practice to optimize the performance by minimizing the initial data scan.
You need to create the query.
In which order should perform the actions? To answer, move all actions from the list of actions to the answer area and arrange them in the correct order.
Correct Answer:

Explanation:
Verified Answer: 1) Select the requests table; 2) apply the 24-hour time filter; 3) filter failed requests; 4) join the dependencies table; 5) summarize average dependency duration by operation.
Detailed Explanation: KQL performs best when high-selectivity filters are applied as early as possible, especially the time predicate that limits the amount of data scanned. Starting from AppRequests, restricting to the last 24 hours, and then filtering failures reduces the left-side dataset before the join. The dependency table is then correlated with those requests, and aggregation is performed last to calculate average dependency duration by operation. Joining or summarizing before the time and failure filters would process more data than necessary.
Study Guide Alignment: Security and operations: Key Vault, App Configuration, managed identity, OpenTelemetry, Azure Monitor, and KQL-based troubleshooting.
Official Microsoft Learn References: AI-200 Study Guide | Optimize log queries in Azure Monitor
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