Microsoft AI-200 actual dump : Developing AI Cloud Solutions on Azure

AI-200
  • Exam Code: AI-200
  • Exam Name: Developing AI Cloud Solutions on Azure
  • Updated: Aug 07, 2026
  • Q & A: 93 Questions and Answers

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Microsoft AI-200 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Develop AI solutions using Azure data services30%- Design and optimize data access and retrieval
  • 1. Indexing strategies, query optimization, and consistency models
  • 2. Implement hybrid search and retrieval patterns
- Implement vector-enabled databases
  • 1. Azure Cosmos DB for NoSQL with vector search
  • 2. Azure Managed Redis for caching, streaming, and vector storage
  • 3. Azure Database for PostgreSQL with pgvector extension
Topic 2: Secure, monitor, and optimize AI solutions20%- Implement observability and reliability
  • 1. OpenTelemetry and Azure Monitor integration
  • 2. Optimize performance, cost, and scalability
  • 3. Logging, metrics, and distributed tracing
- Manage security and configuration
  • 1. Managed identities and access control
  • 2. Azure Key Vault for secrets, keys, and certificates
  • 3. App Configuration for dynamic settings
Topic 3: Develop containerized AI solutions on Azure25%- Implement container hosting environments
  • 1. Deploy to Azure Container Apps and Azure Kubernetes Service (AKS)
  • 2. Azure Container Registry: store, version, manage images
  • 3. Configure scaling, networking, and security for containers
- Monitor and troubleshoot containerized workloads
  • 1. Log analysis, health checks, and performance monitoring
  • 2. Manage configurations and secrets for containers
Topic 4: Integrate backend services and build event-driven architectures25%- 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. Orchestrate AI pipelines and workflows
  • 2. Azure Functions for AI integration and processing

Microsoft Developing AI Cloud Solutions on Azure Sample Questions:

1. You are developing a Java application to be deployed in Azure. The application stores sensitive data in Azure Cosmos DB.
You need to configure Always Encrypted to encrypt the sensitive data inside the application.
What should you do first?

A) Create a new container to include an encryption policy with the JSON properties to be encrypted.
B) Create a Microsoft Entra ID managed identity and assign the identity to a new Azure Key Vault instance.
C) Create a data encryption key (DEK) by using the Azure Cosmos DB SDK and store the key in Azure Cosmos DB.
D) Create a customer-managed key (CMK) and store the key in a new Azure Key Vault instance.


2. Hotspot Question
A Python web API uses OpenTelemetry for tracing. The call_downstream_service function makes an outbound HTTP request by using the requests library.
The following code is the only OpenTelemetry configuration in the application:

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


3. You are developing an AI API deployed to ACA. The API requires database credentials that are stored in Key Vault. Key Vault is configured to use Azure RBAC for access control.
The database credentials are rotated periodically by the security team. The application must always use the latest version of each credential without being redeployed and without exposing secrets in code or configurations.
You need to implement a secure secret access strategy that prevents credential exposure and fetches the latest version of each secret at runtime without redeploying the container.
Which three actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A) Assign a system-assigned managed identity.
B) Configure a Key Vault RBAC role assignment.
C) Retrieve the secret at runtime by using the SDK.
D) Configure a Key Vault access policy.
E) Export the secret during deployment.


4. You are developing an application that must extract structured field data (invoice number, total, vendor name) from scanned invoices in multiple layouts. You need a solution that requires no custom model training. What should you use?

A) Azure AI Vision Read API
B) Azure AI Document Intelligence custom neural model
C) Azure AI Language custom named entity recognition
D) Azure AI Document Intelligence prebuilt invoice model


5. You are developing an AI search API that caches semantic search results in Redis.
Search results must remain cached for 10 minutes. If the underlying data changes, cached entries must NOT be returned.
You need to implement a cache-aside strategy to ensure data consistency.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A) Configure a cache notification for key space events.
B) Implement sliding expiration based on key access.
C) Delete related cache keys when the source data changes.
D) Configure a 10-minute Time to Live on each key.


Solutions:

Question # 1
Answer: D
Question # 2
Answer: Only visible for members
Question # 3
Answer: A,B,C
Question # 4
Answer: D
Question # 5
Answer: C,D

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