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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Secure, monitor, and optimize AI solutions | 20% | - Manage security and configuration
|
| 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% | - Implement messaging and event systems
|
| Topic 4: Develop containerized AI solutions on Azure | 25% | - Implement container hosting environments
|
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NEW QUESTION # 50
An AI application uses a database. The database credential rotates every 30 days.
The application currently requires a manual update each time the credential rotates.
You need to ensure that the application always uses the latest secret version without manual updates.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: A,D
Explanation:
Configure a Key Vault rotation policy to automate periodic credential generation and updates.
Retrieve secrets without a version identifier (versionless reference) so the app automatically resolves the newest active version.
Incorrect:
[Not B]
To stop manual updates, you should not retrieve secrets by specifying a version identifier, because locking in a version stops the application from seeing newer updates.
Reference:
https://learn.microsoft.com/en-us/azure/key-vault/secrets/secure-secrets
NEW QUESTION # 51
Hotspot Question
You deploy a Linux container image to App Service.
The container requires the following environment variables at runtime:
- A non-sensitive configuration value named MODEL_VERSION
- A database password that must remain secure
You need to configure App Service to provide these environment variables at runtime.
Which configurations should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: App setting with plain text value
To provide a non-sensitive environment variable named MODEL_VERSION to a Linux custom container deployed to Azure App Service, you should configure it as an Application Setting (App Setting). In Azure App Service, any custom configuration defined within the Application Settings is automatically injected into Linux containers as an environment variable at runtime.
Box 2: Key Vault reference syntax
You should configure the database password as an Azure Key Vault reference inside App Service Application Settings. This prevents the secret from being stored in plaintext in the app configuration and injects it securely into the container as an environment variable at runtime.
Reference:
https://learn.microsoft.com/en-us/azure/app-service/tutorial-custom-container?tabs=azure-cli&pivots=container-linux
NEW QUESTION # 52
You are designing an Azure Function app that exposes a public API.
The solution must:
Validate incoming request data and return results immediately to the caller.
Support Microsoft Entra ID authentication.
Scale automatically under variable load.
You need to implement a trigger.
Which trigger should you implement?
Answer: A
Explanation:
Detailed Explanation: An HTTP trigger is the only option that directly accepts a synchronous external request and can return a response immediately to the caller. Azure Functions uses HTTP triggers to implement serverless APIs and webhooks, while Microsoft Entra authentication can be applied to the Function App or API surface. Queue, Event Grid, and Service Bus triggers are asynchronous event-processing mechanisms and do not provide the request/response semantics required by this public API scenario.
Study Guide Alignment: Azure service integration: Service Bus, Event Grid, Azure Functions triggers
/bindings, and event-driven processing.
Official Microsoft Learn References: AI-200 Study Guide | Azure Functions HTTP trigger
NEW QUESTION # 53
You optimize an AI inference API that uses Redis caching.
You must reduce the risk of serving outdated data while minimizing cache management overhead.
You need to implement the caching strategy that satisfies the requirements.
What should you do?
Answer: A
Explanation:
Trigger invalidation when source data changes is the best action.
Data Freshness: This is a proactive cache-aside or write-through approach. By explicitly deleting or updating the specific Redis key when the underlying database or model data changes, you completely eliminate the risk of serving stale data.
Low Overhead: It keeps cache management overhead minimal because invalidation logic is execution-dependent (event-driven). Instead of constantly updating expirations or relying on heavy computing logic, you only trigger an action when a write/change event occurs.
Incorrect:
[not B]
Set eviction policy to allkeys-lru:
This policy is a memory management feature, not a data-freshness strategy. It only deletes the Least Recently Used (LRU) keys when your Redis instance runs out of RAM. If memory usage is stable, outdated data will sit in the cache forever, posing a major risk of serving stale inferences.
[not D]
Reset expiration on each read (Sliding TTL):
This actively increases the risk of serving outdated data. If a specific AI response is highly popular and read continuously, its expiration window will extend indefinitely. The data remains stuck in the cache even if the source data undergoes critical updates.
Reference:
https://oneuptime.com/blog/post/2026-01-30-llm-caching-strategies/view
NEW QUESTION # 54
Drag and Drop Question
You are configuring an Azure-hosted AI application that uses Azure App Configuration to manage its runtime settings.
The application must provide the following functionality:
- Support percentage-based, targeted rollouts.
- Maximize token limits per request.
- Store a key that is retrieved securely at runtime.
- Reference a list of supported deployment regions.
You need to configure the App Configuration features for the app.
Which features should you configure? To answer, move the appropriate App Configuration features to the correct configuration items. You may use each App Configuration features once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Feature flag
Use a Feature flag.
Azure App Configuration provides built-in feature management specifically designed to dynamically control application behavior without redeploying code.
Percentage-Based Rollouts: Feature flags support targeting filters (such as the standard Microsoft.Targeting filter), which natively handle percentage-based rollouts and specific audience targeting rules.
Dynamic Changes: You can safely toggle features or change the exposure percentage on the fly directly through the Azure portal or via APIs.
Box 2: Key-value
Key-value is the correct feature to use.
A standard key-value pair is the optimal choice for managing runtime settings like numeric thresholds or token limits.
Direct Data Injection: It allows you to store the specific maximum token limit (e.g., MaxTokensPerRequest = 4096) as an integer or string that your application can parse directly at runtime.
No Extra Overhead: Unlike the other options, a standard key-value pair maps directly to application configuration variables without requiring secondary lookups or conditional logic evaluation.
Box 3: Key Vault reference
Use an Azure Key Vault reference.
Azure App Configuration is optimized for non-sensitive runtime configurations like feature flags, environment names, and general application settings. Sensitive values (such as API keys for OpenAI/LLM models, database passwords, and connection strings) should always be stored natively in Azure Key Vault.
By creating a Key Vault Reference inside Azure App Configuration, you store only the URI pointing to the secret rather than the secret value itself. When your AI application requests configuration data at runtime, the App Configuration provider automatically contacts Key Vault, resolves the reference, and securely injects the actual secret directly into your application's memory pipeline.
Box 4: Key-value
Use a standard configuration key-value pair (or a JSON array within a key).
How to store it: Save the regions as a comma-separated string or a JSON array under a single key.
Key Example: Deployment:SupportedRegionsValue Example: ["eastus", "westeurope",
"southeastasia"]
Content Type: Set the content type to application/json so your application can automatically parse it into a list or array at runtime.
Reference:
https://learn.microsoft.com/en-us/azure/azure-app-configuration/manage-feature-flags
https://turbo360.com/blog/get-azure-key-value-pairs-from-app-configuration
https://learn.microsoft.com/en-us/azure/app-service/app-service-key-vault-references
NEW QUESTION # 55
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