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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Secure, monitor, and optimize AI solutions | 20% | - Implement observability and reliability
|
| Topic 2: Develop containerized AI solutions on Azure | 25% | - Monitor and troubleshoot containerized workloads
|
| Topic 3: Develop AI solutions using Azure data services | 30% | - Implement vector-enabled databases
|
| Topic 4: Integrate backend services and build event-driven architectures | 25% | - Implement messaging and event systems
|
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NEW QUESTION # 131
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
Explanation:
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.
NEW QUESTION # 132
An AI platform uses App Configuration for feature flags and endpoint routing.
The platform stores secrets alongside configuration data and does NOT support dynamic configuration refresh.
You need to redesign the configuration approach so that:
configuration supports dynamic refresh;
secrets are stored outside App Configuration;
the application can securely access both App Configuration and Key Vault.
You need to enable secure dynamic configuration management for the platform.
Which three actions should you perform? Each correct answer presents part of the solution. Choose three.
NOTE: Each correct selection is worth one point.
Answer: A,B,C
Explanation:
Detailed Explanation: The original answer omitted the secret-storage requirement. API keys and other secrets should be held in Key Vault, while App Configuration should retain non-secret configuration and Key Vault references. Dynamic refresh is implemented through the App Configuration refresh/polling mechanism rather than requiring an application restart. Managed identity provides credential-free access to both services in Azure. Environment variables do not provide centralized dynamic refresh, and a stored service-principal secret creates exactly the credential-management problem the design is intended to eliminate.
Study Guide Alignment: Security and operations: Key Vault, App Configuration, managed identity, OpenTelemetry, Azure Monitor, and KQL-based troubleshooting.
Official Microsoft Learn References: AI-200 Study Guide | Dynamic configuration in ASP.NET Core | Use Key Vault references in App Configuration | Managed identities for Azure resources
NEW QUESTION # 133
You are designing an Azure Function app that processes large image uploads submitted by users through an HTTP endpoint.
The solution must:
- Prevent client timeouts by decoupling image processing from the
initial upload request.
- Support automatic retry behavior for failed processing attempts.
- Scale the background processing independently of the rate of incoming HTTP uploads.
You need to design a scalable and reliable asynchronous processing solution.
Which two actions should you implement? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: A,B
Explanation:
To build a scalable and reliable asynchronous solution that meets the requirements, you should use an HTTP-triggered function to save images to Azure Blob Storage and enqueue a message, then use a Queue-triggered function to process the image.
1. Decouple via Queue Messaging
HTTP Function: Receives the initial user upload, saves the large image file directly to Azure Blob Storage, and writes a small metadata message (e.g., the blob URI) into an Azure Storage Queue or Azure Service Bus Queue.
Instant Response: The HTTP function immediately returns a 202 Accepted status to the client along with a status-tracking URL. This completely eliminates client timeout issues by shifting heavy work to the background.
2. Leverage Built-In Queue Triggers
Queue-Triggered Function: A second, separate Azure Function is configured to trigger whenever a new message lands in the queue. It downloads the image from Blob Storage and performs the processing.
Automatic Retries: Azure Queue storage and Service Bus triggers feature native retry behavior. If the processing function fails or crashes, the message is automatically returned to the queue to be retried. Persistent failures are automatically moved to a Poison Queue (Dead Letter Queue) after a configured number of attempts (default is 5).
Independent Scaling: Under the Azure Consumption or Premium plan, the Queue-triggered function scales its instances up or down based on the queue length (the backlog of images to process). This scales independently of the HTTP-triggered function, which scales purely based on incoming request volume.
Reference:
https://oneuptime.com/blog/post/2026-02-16-azure-functions-python-http-triggers-blob-storage/view
NEW QUESTION # 134
Hotspot Question
You are developing an AI application that retrieves database credentials from Key Vault by using the Azure SDK for Python.
The application must use managed identity for authentication.
You review the following code segment that retrieves a secret from Key Vault.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: No
No, this code will not retrieve the latest version of dbPassword.
Instead, it explicitly retrieves the specific version designated by the string "123".
To pull the latest active version of a secret, omit the version parameter entirely from the get_secret function.python# Change this line:
secret = client.get_secret("dbPassword", version="123")
# To this line:
secret = client.get_secret("dbPassword")
Box 2: Yes
Yes, the code will successfully authenticate to Azure Key Vault without storing client secrets when deployed to an Azure-hosted environment with a managed identity enabled.
DefaultAzureCredential Behavior: This class is a sequential chaining credential mechanism.
When deployed to Azure (such as Azure App Service, Azure VMs, or Azure Functions), it automatically looks for an active Managed Identity environment endpoint to fetch an access token.
Zero Secret Storage: Because the platform relies on the underlying Azure host infrastructure to handle identity token generation, you do not need to hardcode client secrets, passwords, or certificates anywhere inside your application code or configuration settings.
Box 3: No
No, subsequent calls to this code will not retrieve the new version.
By explicitly including version="123" in the get_secret method, you are requesting a specific immutable version of the secret.
Reference:
https://learn.microsoft.com/en-us/azure/key-vault/secrets/quick-create-python
NEW QUESTION # 135
You are building o back end pipeline that receives Al inference requests. The pipeline must perform the following actions:
* Publish a message so that multiple independent consumers receive it.
* Process massages in order through a single consumer entity.
* isolate any failed messages
You need to configure the appropriate Service Bus entities.
How should you configure the service bus entities? To answer, move the appropriate configurations to the correct requirements. You may use each configuration once..
Answer:
Explanation:
Explanation:
NEW QUESTION # 136
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