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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Develop containerized AI solutions on Azure | 25% | - Monitor and troubleshoot containerized workloads
|
| Topic 2: Develop AI solutions using Azure data services | 30% | - Implement vector-enabled databases
|
| Topic 3: Integrate backend services and build event-driven architectures | 25% | - Build serverless APIs and workflows
|
| Topic 4: Secure, monitor, and optimize AI solutions | 20% | - Manage security and configuration
|
Experts at Actualtests4sure have also prepared Microsoft AI-200 practice exam software for your self-assessment. This is especially handy for preparation and revision. You will be provided with an examination environment and you will be presented with actual Microsoft AI-200 Exam Questions.
NEW QUESTION # 45
You maintain multiple versions of a container image in Azure Container Registry.
The production deployment must always run the exact same image build even if tags are changed later.
You need to ensure predictable and immutable image selection during deployment.
What should you do?
Answer: C
Explanation:
Use the image ' s SHA-256 manifest digest when defining the production deployment. Azure Container Registry assigns every pushed image manifest a unique digest, and Microsoft explicitly states that pulling an image by digest guarantees the image version being retrieved , even if an identically named tag is later pushed to a different image. A digest reference has the form myregistry.azurecr.io/repository@sha256: < digest > .
Tags such as production or latest are mutable references . By default, a user or pipeline with sufficient permissions can push a different image under the same tag. Microsoft therefore warns against relying on reusable stable tags for production deployments when exact image reproducibility is required.
A scheduled rebuild also creates a new image artifact and therefore cannot guarantee that production executes the original build. In contrast, the manifest digest is content-addressed and resolves to the precise image manifest selected at deployment time.
Thus, for deterministic and immutable production image selection, reference the container image by its SHA digest rather than by a mutable tag .
Study Guide references: Azure Container Registry # image manifests and digests; image addressing; tagging
/versioning recommendations; immutable deployment references.
NEW QUESTION # 46
You plan to deploy a container to an Azure App Service API app named api1. You host the source code for api1 in a GitHub repository. The container uses the API key at runtime to connect to a backend service.
The container must be able to retrieve the API key at runtime without exposing it in the source repository or Git commit history. The API key must not be stored in application configuration directly. The API key must be accessed securely from Azure Key Vault.
You need to ensure that the API key is stored securely in Azure Key Vault and is available to the container at runtime without being exposed in source control or Git commit history.
Solution: Store the API key as a GitHub repository secret.
Does the solution meet the goal?
Answer: A
NEW QUESTION # 47
You are designing a messaging solution by using Service Bus for AI document processing.
You need to ensure that a published message is delivered to multiple independent consumers.
Each consumer must receive their own copy of the message.
Which two Service Bus entities should you use? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: B,E
Explanation:
Topics and Subscriptions are the two Azure Service Bus entities that fit this scenario.
Topics: The publisher sends the document processing message to a single topic, which acts as the central distribution hub.
Subscriptions: Each independent consumer creates its own individual subscription under that topic. When a message arrives, a copy is forwarded to every independent subscription so each consumer can process their own copy safely and separately.
Reference:
https://learn.microsoft.com/en-us/azure/service-bus-messaging/service-bus-queues-topics-subscriptions
NEW QUESTION # 48
A customer support bot built with Azure AI Foundry Agent Service must ground its answers strictly in an internal knowledge base and avoid hallucinating unsupported facts.
What should you implement?
Answer: B
Explanation:
Connect the agent to an Azure AI Search knowledge source and explicitly constrain its instructions to answer from retrieved evidence. Microsoft Foundry Agent Service can use Azure AI Search to retrieve proprietary organizational content and ground model responses in that content. Retrieved documents provide the factual context from which the model generates its answer, and Azure AI Search can return source references for attribution.
Microsoft ' s RAG guidance also specifically recommends using clear system instructions that require the model to stay within retrieved content when hallucination risk must be reduced. If the available evidence does not support an answer, the instructions should direct the agent to state that the information is unavailable rather than inventing facts. Retrieval grounding substantially reduces unsupported generation, although production systems should still evaluate outputs because grounding alone does not mathematically guarantee zero hallucinations.
Increasing temperature would generally increase output variability and is contrary to the objective. A larger context window without retrieval does not give the model access to the organization ' s internal knowledge base. Disabling content filtering weakens safety controls and has no role in factual grounding.
Study Guide references: Microsoft Foundry Agent Service # Azure AI Search tool; RAG grounding; knowledge sources; source attribution; grounding instructions.
NEW QUESTION # 49
You are developing an Azure Functions app.
All functions in the app meet the following requirements:
Run until either a successful run or until 10 run attempts occur.
Ensure that there are at least 20 seconds between attempts for up to 15 minutes.
You need to configure the host.json file.
How should you complete the code segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
NEW QUESTION # 50
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