Microsoft Developing AI Cloud Solutions on Azure : AI-200

  • Exam Code: AI-200
  • Exam Name: Developing AI Cloud Solutions on Azure
  • Updated: Sep 12, 2026
  • Q & A: 144 Questions and Answers

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Microsoft AI-200 Exam Syllabus Topics:

SectionWeightObjectives
Secure, monitor, and optimize AI solutions20%- Implement observability and reliability
  • 1. Logging, metrics, and distributed tracing
  • 2. OpenTelemetry and Azure Monitor integration
  • 3. Optimize performance, cost, and scalability
- Manage security and configuration
  • 1. App Configuration for dynamic settings
  • 2. Azure Key Vault for secrets, keys, and certificates
  • 3. Managed identities and access control
Develop AI solutions using Azure data services30%- Design and optimize data access and retrieval
  • 1. Implement hybrid search and retrieval patterns
  • 2. Indexing strategies, query optimization, and consistency models
- Implement vector-enabled databases
  • 1. Azure Managed Redis for caching, streaming, and vector storage
  • 2. Azure Cosmos DB for NoSQL with vector search
  • 3. Azure Database for PostgreSQL with pgvector extension
Develop containerized AI solutions on Azure25%- 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. Azure Container Registry: store, version, manage images
  • 2. Deploy to Azure Container Apps and Azure Kubernetes Service (AKS)
  • 3. Configure scaling, networking, and security for containers
Integrate backend services and build event-driven architectures25%- Build serverless APIs and workflows
  • 1. Orchestrate AI pipelines and workflows
  • 2. Azure Functions for AI integration and processing
- Implement messaging and event systems
  • 1. Azure Service Bus for reliable messaging
  • 2. Azure Event Grid for event-driven processing
  • 3. Connect services and expose APIs securely

Microsoft Developing AI Cloud Solutions on Azure Sample Questions:

Question #1

You deploy a production Azure Function app that connects to an Azure SQL Database.
The solution must provide the following functionality:
* Prevent secrets from being exposed in source control.
* Support secret rotation without redeploying the function app.
* Avoid downtime during credential updates.
You need to configure secure and maintainable secret management. What should you configure?

  • A. Environment variables in local.settings.json
  • B. Hard coded connection string in the startup class
  • C. Application settings with Key Vault references
  • D. Parameter file stored in source control
Answer: C

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Question #2

You deploy multiple instances of a change feed processor to handle a high ingestion rate within Azure Cosmos DB for NoSQL.
Each processor instance must process a different subset of partitions.
You need to ensure the workload is load-balanced across all processor instances.
What should you configure?

  • A. strong consistency
  • B. lease container
  • C. autoscale throughput
  • D. indexing precision
Answer: B

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Question #3

You are reviewing an Azure Function app that processes incoming order requests for a company. The function must:
* Accept order submissions from an external client application.
* Require controlled access for security
* Return a response containing the processed request payload.

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:


Explanation:

Verified Answer: Yes; No; Yes; No.
Detailed Explanation: `auth_level=FUNCTION` means invocation requires a function key unless a stronger platform authentication layer is configured, so the first statement is true. The route explicitly permits POST, not GET. The function reads `req.get_body()` and returns that value in the HttpResponse, so the response contains the request body. No schema, type, required-field, or other payload validation is performed before the response is constructed, making the final statement false.
Study Guide Alignment: Azure service integration: Service Bus, Event Grid, Azure Functions triggers
/bindings, and event-driven processing.
Official Microsoft Learn References: AI-200 Study Guide | Azure Functions HTTP trigger

Question #4

You need to configure the database resources for the Azure Database for PostgreSQL instance.
How should you complete the configuration to meet the business and technical requirements? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:


Explanation:
* Meet the 200-ms semantic search latency requirement: Increase compute vCores.
* Optimize the environment for high-dimensional pgvector index residency: Increase memory allocation.
* Support the continuous ingestion of transaction-based embeddings: Enable storage autoscale.
For the strict sub-200-ms vector-search latency target, increasing compute vCores is the appropriate choice.
Vector similarity operations are computationally intensive, and additional CPU capacity improves mathematical throughput and parallel query execution. Microsoft's pgvector guidance emphasizes query-plan optimization, ANN indexes such as HNSW, and sufficient compute resources when optimizing vector workloads.
For high-dimensional pgvector index residency , increase memory allocation . HNSW provides strong query-performance characteristics but consumes more memory than IVFFlat. Keeping frequently accessed vector index structures in memory minimizes disk access and materially improves latency. Microsoft explicitly notes that HNSW requires more memory while providing a better speed/recall tradeoff.
For the continuous ingestion of millions of embeddings, enable storage autoscale . Azure Database for PostgreSQL Flexible Server can automatically increase allocated storage as capacity approaches configured thresholds, avoiding an out-of-storage condition as data volumes grow. Microsoft recommends storage autogrow for workloads whose storage demand can increase dynamically.
Increasing max_connections does not directly improve vector computation or index residency, read replicas primarily scale reads, and backup retention does not address ingestion capacity.
Study Guide references: Azure Database for PostgreSQL Flexible Server # pgvector performance optimization; compute and memory sizing; HNSW indexing; storage autogrow.

Question #5

You process Azure Service Bus messages that require a dependent external API call.
If the API is temporarily unavailable, you must delay processing of the message without incrementing the delivery count. You need to find a way to process the message when the API is available while keeping the message accessible. Which message action should you perform?

  • A. Defer
  • B. Abandon
  • C. Dead-letter
  • D. Complete
Answer: A

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