Microsoft AI-200 Practice Exam Questions

Microsoft AI-200 Sample Question Answers

Question # 1

For a production AI platform you must achieve end-to-end observability: correlate a user request across an API, a queue, a worker, and model/database calls; alert on latency and error-rate SLOs; and control telemetry cost. Which combination best delivers this?

A.  Autoscale provisioned throughput 
B.  Manual (standard) provisioned throughput sized to the steady load
C.  Serverless 
D.  Strong consistency 

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Question # 2

You must evaluate whether a new RAG prompt/version improves answer quality before rolling it out to all users, using production-like traffic and objective metrics such as groundedness and relevance. Which approach is best?

A.  Only test with a handful of manual prompts once 
B.  Deploy the new version to 100% of users immediately and watch for complaints 
C.  Rely solely on unit tests of the code
D.  Run an A/B test routing a portion of traffic to the new version and compare evaluation metrics (groundedness, relevance, latency, cost) before full rollout 

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Question # 3

An application intermittently fails to read a rotated secret from Key Vault with '403 Forbidden', but only from certain instances. The identity has the correct role. What should you investigate first?

A. The container image size
B. Key Vault network/firewall settings and private endpoint/VNet configuration for the affected instances, plus RBAC propagation delay
C. The Service Bus lock duration
D. The model deployment quota

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Question # 4

A security review requires that no application secrets, connection strings, or keys exist anywhere in code, pipelines, or app settings across your AI solution. Which end-to-end approach best satisfies this?

Rotate keys weekly but keep them in app settings
Put secrets in a private Git repository
Store all secrets as encrypted environment variables in the image
Use managed identities for service-to-service auth (RBAC), Key Vault for the few unavoidable secrets with Key Vault references, and Entra tokens instead of keys

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Question # 5

Costs for your Azure OpenAI-backed feature are rising sharply. Investigation shows long prompts with large retrieved context and high max_tokens, plus many repeated identical requests. Which combination best reduces token cost without degrading answer quality?

A. Send the full document corpus in every prompt
B. Trim/re-rank retrieved context to the most relevant chunks, cap max_tokens sensibly, and add a response cache for repeated queries
C. Raise temperature and top_p
D.  Disable retrieval entirely 

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Question # 6

Your application receives HTTP 401 from Azure OpenAI after migrating from API keys to managed identity. The managed identity exists and the endpoint is correct. What is the most likely missing step?

A. The model deployment name is wrong
B. The region is not supported
C. The managed identity has not been granted the 'Cognitive Services OpenAI User' role on the resource, orthe client is not requesting an Entra token 
D. The request uses too many tokens

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Question # 7

A high-throughput ingestion endpoint must accept millions of telemetry events per hour for later AI analysis, buffering them durably for stream processing. Given the AI-200 messaging options, which service is the best fit for high-volume event streaming ingestion

Azure Service Bus queue with sessions
 Azure App Configuration
Azure Event Hubs (event streaming) as the ingestion buffer
A single Cosmos DB item updated repeatedly

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Question # 8

An Event Grid-triggered function must process events exactly in the order they occurred for a given entity, but events are arriving out of order. What is the correct understanding and remedy?

A. Increase the Event Grid retry count to fix ordering
B. Enable duplicate detection to restore order
C. Event Grid guarantees ordering; the function code is buggy
D. Event Grid does not guarantee ordered delivery; use Service Bus sessions (or add sequence numbers and reorder) to enforce per-entity ordering

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Question # 9

You are designing idempotent processing for an at-least-once messaging pipeline feeding an AI enrichment step. Which two practices help ensure duplicate deliveries do not cause duplicate side effects? (Choose two.) 

A. Increase the model temperature for variety
B. Make write operations idempotent using deterministic keys/upserts
C. Use ReceiveAndDelete so messages are never redelivered
D. Track processed message IDs (for example, in Cosmos DB or Redis) and skip already-seen IDs

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Question # 10

An Azure Function on the Consumption plan experiences cold-start latency that violates a strict p99 requirement for a customer-facing AI endpoint, and it must also reach resources over a private VNet. Which change best addresses both concerns?

A. Increase function timeout
B. Move to the Premium plan (pre-warmed instances and VNet integration)
C. Keep Consumption plan and add more logging
D. Switch to a Timer trigger

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