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| Section | Objectives |
|---|---|
| Topic 1: Develop AI solutions by using Azure data management services | - Work with Azure data platforms for AI workloads
|
| Topic 2: Connect to and consume Azure services | - Integrate Azure services
|
| Topic 3: Develop containerized solutions on Azure | - Implement containerized applications
|
| Topic 4: Secure, monitor, troubleshoot Azure solutions | - Operate AI cloud solutions
|
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NEW QUESTION # 14
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You must reduce the risk of serving outdated data while minimizing cache management overhead.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: D
Explanation:
Detailed Explanation: If the priority is to minimize stale results, source-driven invalidation is the direct control: when the underlying record changes, delete the corresponding cache entry so the next request repopulates it from current data. Sliding expiration can keep a frequently accessed stale item alive, disabling expiration is worse, and an allkeys-LRU policy evicts according to memory pressure rather than data freshness. Invalidation therefore best addresses correctness without requiring constant cache-wide maintenance.
Study Guide Alignment: AI data-management workloads: Cosmos DB, PostgreSQL, caching, vector storage, vector retrieval, consistency, and connection optimization.
Official Microsoft Learn References: AI-200 Study Guide | Azure Managed Redis documentation
NEW QUESTION # 15
You are reviewing the message processing code in a backend worker service.
You review the following Python code that initializes and starts a Service Bus processor
Answer:
Explanation:
Explanation:
Verified answer: No; Yes; No.
Detailed Explanation: The default Service Bus receive behavior is PeekLock rather than receive-and-delete, so merely receiving a message does not remove it from the queue; it must be settled successfully. If processing fails and the message remains unsettled or the lock is lost, it can become available for another delivery. Invalid JSON, however, is an application-level content problem: Service Bus does not inspect the payload as JSON and automatically retry it to MaxDeliveryCount solely because deserialization fails. The application's settlement/error path determines what happens.
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 | Service Bus message transfers, locks, and settlement | Service Bus messages, routing, and correlation
NEW QUESTION # 16
Hotspot Question
You are creating an Azure Functions app project in your local development environment by using Azure Functions Core Tools.
You must create the project in either Python or C# without using a template.
You need to specify the command and its parameter required to create the Azure Functions app project.
Which command and parameter should you specify? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: func init
To initialize a new Azure Functions app project from the command line using Azure Functions Core Tools without using a specific code template, use the func init command combined with the -
-worker-runtime parameter.
Box 2: --worker-runtime
Reference:
https://r-vm.com/python-on-azure-functions
NEW QUESTION # 17
You process Azure Service Bus messages that require a dependent external API call.
If the API is temporarily unavailable, you must delay processing of the message without incrementing the delivery count. You need to find a way to process the message when the API is available while keeping the message accessible. Which message action should you perform?
Answer: D
NEW QUESTION # 18
You plan to deploy a web app to App Service on Linux. You create an App Service plan. You create and push a custom Docker image that contains the web app to Azure Container Registry.
You need to access the console logs generated from inside the container in real-time.
How should you complete the Azure CLI command? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
nable container logging with `az webapp log config --docker-container-logging filesystem`, then stream it with `az webapp log tail`.
Detailed Explanation: The Azure CLI exposes separate operations for enabling App Service container logging and viewing the live stream. For a custom Linux container, docker/container logging must first be written to the App Service filesystem. The `az webapp log tail` command then starts real-time log tracing.
Commands such as `show` or `download` inspect configuration or retrieve historical files; they do not provide the requested live stream from the running container.
Study Guide Alignment: Containerized Azure workloads: registry builds, App Service containers, Container Apps revision/scaling behavior, and AKS deployment choices.
Official Microsoft Learn References: AI-200 Study Guide | Azure CLI: az webapp log
NEW QUESTION # 19
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