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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
- 1. Log analysis, health checks, and performance monitoring
- 2. Manage configurations and secrets for containers
- Implement container hosting environments
- 1. Configure scaling, networking, and security for containers
- 2. Azure Container Registry: store, version, manage images
- 3. Deploy to Azure Container Apps and Azure Kubernetes Service (AKS)
|
| Topic 2: Develop AI solutions using Azure data services | 30% | - Implement vector-enabled databases
- 1. Azure Database for PostgreSQL with pgvector extension
- 2. Azure Cosmos DB for NoSQL with vector search
- 3. Azure Managed Redis for caching, streaming, and vector storage
- Design and optimize data access and retrieval
- 1. Indexing strategies, query optimization, and consistency models
- 2. Implement hybrid search and retrieval patterns
|
| Topic 3: Integrate backend services and build event-driven architectures | 25% | - Implement messaging and event systems
- 1. Connect services and expose APIs securely
- 2. Azure Event Grid for event-driven processing
- 3. Azure Service Bus for reliable messaging
- Build serverless APIs and workflows
- 1. Azure Functions for AI integration and processing
- 2. Orchestrate AI pipelines and workflows
|
| Topic 4: Secure, monitor, and optimize AI solutions | 20% | - Manage security and configuration
- 1. Managed identities and access control
- 2. App Configuration for dynamic settings
- 3. Azure Key Vault for secrets, keys, and certificates
- Implement observability and reliability
- 1. Optimize performance, cost, and scalability
- 2. OpenTelemetry and Azure Monitor integration
- 3. Logging, metrics, and distributed tracing
|
Microsoft Developing AI Cloud Solutions on Azure Sample Questions:
1. You are designing an Azure Function that will process orders from a new Azure Service Bus queue.
You need to prevent the system from processing messages more than once and preserve failed messages for investigation.
Which two actions should you implement? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A) Enable duplicate detection on the queue.
B) Process orders by using an HTTP trigger.
C) Include a dead-letter handling process.
D) Enable sessions on Service Bus.
2. Your solution must answer questions about numeric data in large Excel-based reports (e.g.,
"What was Q3 revenue for the West region?"). Which approach is most appropriate?
A) Store the Excel data as unstructured text and embed it for vector search
B) Rely on the model's parametric knowledge
C) Use Azure AI Vision to read the spreadsheet as an image
D) Convert data to a structured table/SQL source and use a function-calling agent to query it
3. An application performs similarity search across 5 million embeddings stored in Azure Database for PostgreSQL with pgvector. Queries often filter by department before ranking by cosine distance.
P95 latency for vector similarity queries exceeds the SLA target. Monitoring shows sustained high CPU use during query execution.
You need to reduce P95 latency for filtered vector similarity queries.
What should you do?
A) Store embeddings as JSON.
B) Increase statement timeout.
C) Create B-tree indexes on frequently filtered metadata columns.
D) Increase embedding dimensionality.
4. Hotspot Question
You plan to deploy a web app to App Service on Linux. You create an App Service plan. You create and push a custom Docker image that contains the web app to Azure Container Registry.
You need to access the console logs generated from inside the container in real-time.
How should you complete the Azure CLI command? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

5. 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.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear on the review screen.
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.
You need to ensure that the API key remains outside of Git commit history and is available to the container at runtime.
Solution: Store the API key in Azure Key Vault and reference it from an App Service application setting.
Does the solution meet the goal?
A) Yes
B) No
Solutions:
Question # 1 Answer: A,C | Question # 2 Answer: D | Question # 3 Answer: C | Question # 4 Answer: Only visible for members | Question # 5 Answer: A |