Developing AI Cloud Solutions on Azure: AI-200 Exam


"Developing AI Cloud Solutions on Azure", also known as AI-200 exam, is a Microsoft Certification. With the complete collection of questions and answers, Pass4sureCert has assembled to take you through 93 Q&As to your AI-200 Exam preparation. In the AI-200 exam resources, you will cover every field and category in Azure AI Engineer Associate Certification helping to ready you for your successful Microsoft Certification.

  • Exam Code: AI-200
  • Exam Name: Developing AI Cloud Solutions on Azure
  • Total Questions: 93

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Microsoft AI-200 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Develop AI solutions using Azure data services30%- Implement vector-enabled databases
  • 1. Azure Managed Redis for caching, streaming, and vector storage
  • 2. Azure Database for PostgreSQL with pgvector extension
  • 3. Azure Cosmos DB for NoSQL with vector search
- Design and optimize data access and retrieval
  • 1. Implement hybrid search and retrieval patterns
  • 2. Indexing strategies, query optimization, and consistency models
Topic 2: 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 Event Grid for event-driven processing
  • 2. Connect services and expose APIs securely
  • 3. Azure Service Bus for reliable messaging
Topic 3: Develop containerized AI solutions on Azure25%- Implement container hosting environments
  • 1. Deploy to Azure Container Apps and Azure Kubernetes Service (AKS)
  • 2. Configure scaling, networking, and security for containers
  • 3. Azure Container Registry: store, version, manage images
- Monitor and troubleshoot containerized workloads
  • 1. Manage configurations and secrets for containers
  • 2. Log analysis, health checks, and performance monitoring
Topic 4: Secure, monitor, and optimize AI solutions20%- 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. OpenTelemetry and Azure Monitor integration
  • 2. Logging, metrics, and distributed tracing
  • 3. Optimize performance, cost, and scalability

Microsoft Developing AI Cloud Solutions on Azure Sample Questions:

1. You develop a message-processing service deployed to Azure Container Apps. The service reads messages from an Azure Service Bus queue.
The solution must minimize costs by ensuring NO compute resources are consumed when the queue is empty.
You need to configure scaling for the service.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A) Enable HTTP ingress concurrency scaling.
B) Configure the scaling rule to allow for the termination of all active replicas.
C) Configure a Kubernetes Event-driven Autoscaler rule that monitors queue length.
D) Increase the scaling rule to allow for the maximum running replica count.


2. Hotspot Question
You are using Python SDK to develop a containerized AI application that retrieves the value of a runtime setting stored in an Azure App Configuration resource. The application will run in Azure in the security context of a managed identity.
The application must work in a local development environment without any code changes.
You need to complete the code that implements the retrieval.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.


3. Drag and Drop Question
You are developing a .NET application that uses Azure Cosmos DB for NoSQL to store application data.
The application uses the Azure Cosmos DB for NoSQL SDK to interact with the database account.
The application must perform the following tasks:
- Initialize the connection by using the account endpoint and key.
- Define shared throughput.
- Perform create, read, update, and delete (CRUD) operations on items
stored in a container.
You need to implement the SDK components required for the application to access and manage data in Azure Cosmos DB for NoSQL.
Which SDK components should you use? To answer, move the appropriate components to the correct requirements. You may use each component 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.


4. 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) Increase statement timeout.
B) Store embeddings as JSON.
C) Increase embedding dimensionality.
D) Create B-tree indexes on frequently filtered metadata columns.


5. Hotspot Question
You are reviewing the Python tracing configuration for an application that must send distributed traces to Azure Monitor.
The following code configures OpenTelemetry tracing:

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


Solutions:

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

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