Microsoft Developing AI Cloud Solutions on Azure AI-200 Exam Questions

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Total 142 questions
Question 1

You deploy an AI application across multiple Azure regions.

The application must be able to view writes across all regions within a predictable time window.

You need to determine the appropriate consistency level.

What are two consistency levels you can use to achieve the goal? Each correct answer presents a complete solution. Choose two.

NOTE: Each correct selection is worth one point.



Answer : A, C


Question 2

You need to deploy Azure function resources and apps by using an automated, version-controlled CI/CD pipeline that supports declarative infrastructure deployment. What should you use?



Answer : B

Detailed GitHub Actions is the correct orchestration mechanism among the options because the case requires an automated, version-controlled pipeline and Bicep-based declarative deployment. Microsoft documents GitHub Actions as a supported way to deploy Bicep and automate Azure resource deployment. Local Git, Azure Functions Core Tools, and Azure CLI can participate in development or scripted deployment, but they do not by themselves satisfy the stated requirement for a repository-driven, repeatable CI/CD pipeline.

Study Guide Alignment: Security and operations: Key Vault, App Configuration, managed identity, OpenTelemetry, Azure Monitor, and KQL-based troubleshooting.

Official Microsoft Learn Reference: AI-200 Study Guide | Deploy Bicep with GitHub Actions | Automate Function app resource deployment


Question 3

An application deployed to AKS depends on an internal API hosted in the same cluster. All pods are healthy and report Ready status, but requests between the services time out.

You need to determine whether the issue is related to Kubernetes service configuration or application code.

What should you do first?



Answer : A


Question 4

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 : D

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.


Question 5

You have container source code stored in a Git repository.

The container registry must automatically build and store a new container image whenever a developer commits code to the Git repository.

You must minimize the use of an external build infrastructure.

You need to configure Azure Container Registry (ACR) to manage the build process natively and automatically.

Which two ACR components should you use? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.



Answer : B, D

Azure Container Registry Tasks provides Azure-hosted container build capabilities, eliminating the need to maintain external Docker build servers or dedicated CI build infrastructure. A Quick task uses commands such as az acr build to send the build context to ACR-managed compute, where Azure builds the container image and, by default, pushes the successfully built image directly into the registry. Microsoft describes quick tasks as cloud-based, on-demand build-and-push operations that do not require a local Docker Engine.

For automatic execution after source-code changes, use a Source-triggered task. ACR Tasks can associate a task with a GitHub or Azure Repos repository and automatically execute the image build whenever code is committed to the configured branch. Microsoft documents that when a commit occurs, the source-control trigger causes ACR Tasks to build and push the resulting image.

A Webhook is not the required standalone ACR build component here. ACR Tasks creates and manages the necessary source-repository webhook as part of configuring the source trigger. An Artifact Cache rule caches upstream container artifacts and does not build application images from Git commits.

Study Guide references: Azure Container Registry Tasks Quick tasks; Automatically triggered tasks; Source-code commit triggers; cloud-based image builds.


Question 6

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals.

You are using Azure Monitor Application Insights to investigate a production API. You open the Logs blade and set the time range to Last 24 hours.

An engineer recommends the following query to count requests by result code and sort the results from most frequent to least frequent:

requests

| summarize request_count = count() by resultCode

| order by request_count desc

You need to determine whether the query returns the number of requests grouped by result code and sorted from most to least frequent.

Solution: The query lists every individual request along with its result code.

Does the solution meet the goal?



Answer : B

The solution statement is incorrect because the KQL query does not return every individual request. The summarize operator aggregates input records according to the grouping expression. In this query, count() calculates the number of request records in each group, while by resultCode creates one group for every distinct HTTP result code represented in the selected Application Insights time range. Microsoft documents that summarize produces one output row for each distinct combination of its by expressions.

The resulting dataset therefore contains columns equivalent to resultCode and request_count, not individual request rows. The subsequent order by request_count desc sorts those aggregate groups in descending order, placing the most frequent result code first. Microsoft provides essentially the same Application Insights pattern for displaying the distribution of requests by result code: summarize request counts by result code and order the resulting counts descending.

If the intent were to list individual requests, the query would omit summarize and typically use project to select fields such as timestamp, operation name, and result code.

Therefore, because the proposed solution incorrectly describes the query as listing each individual request, the answer is No.

Study Guide references: Azure Monitor Logs; Application Insights requests; KQL summarize; count(); grouping; descending sorting.

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Question 7

You are implementing an application by using Azure Event Grid to push near-real-time information to customers.

You have the following requirements:

* You must send events to thousands of customers that include hundreds of various event types.

* The events must be filtered by event type before processing.

* Authentication and authorization must be handled by using Microsoft Entra ID.

* The events must be published to a single endpoint

You need to implement Azure Event Grid

Solution: Publish events to a custom topic. Create an event subscription for each customer.

Does the solution meet the goal?



Answer : B

Detailed A single custom topic is a user-defined publishing endpoint, but creating thousands of customer subscriptions on one custom topic is not the architecture Microsoft provides for managing thousands of isolated topics behind one publisher endpoint. An Event Grid domain is the service construct designed for that scale and partitioning model. The requirement for Microsoft Entra authentication can also be satisfied when publishing to Event Grid resources, but the custom-topic design still misses the domain-level multi-topic requirement.

Study Guide Alignment: Azure service integration: Service Bus, Event Grid, Azure Functions triggers/bindings, and event-driven processing.

Official Microsoft Learn Reference: AI-200 Study Guide | Azure Event Grid event domains | Authenticate Event Grid publishing with Microsoft Entra ID


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Total 142 questions