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Microsoft AI-200 Exam Syllabus Topics:

Microsoft Developing AI Cloud Solutions on Azure Sample Questions:

1. 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 access policy.
C) Configure a Key Vault RBAC role assignment.
D) Retrieve the secret at runtime by using the SDK.
E) Export the secret during deployment.

2. A large retail company operates online and physical stores. The company tracks inventory levels in real time to manage stock efficiently across all locations. You develop an Azure Event Grid solution to handle events generated by the inventory management system deployed to Azure.
You need to implement a subscription filter that dynamically adjusts to seasonal changes in product demand.
Which event filter should you use?

A) A subscription filter that uses a label filter to include events tagged with seasonal promotional codes
B) A prefix filter on the event type field that matches the current season's name
C) A static subject filter that targets events with a subject ending in "/seasonal/inventory"
D) An advanced filter using a Boolean condition that evaluates multiple data fields, including a season field within the event data

3. You store embeddings in Redis by using keys formatted as doc:(id). Some embeddings are accessed frequently. Others are rarely used.
You need to implement a caching strategy that keeps only frequently accessed embeddings in memory.
What should you use?

A) time-window expiration
B) volatile-ttl
C) allkeys-lru
D) EXPIRE command

4. A development team wants to compare multiple prompt variations against the same test dataset and visualize which prompt performs best. What should they use in Azure AI Foundry?

A) Speech Studio custom voice
B) Prompt flow with variants
C) Azure AI Search indexers
D) Model deployment quota management

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

Solutions: