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| Section | Objectives |
|---|---|
| Secure, monitor, troubleshoot Azure solutions | - Operate AI cloud solutions
|
| Develop containerized solutions on Azure | - Implement containerized applications
|
| Connect to and consume Azure services | - Integrate Azure services
|
| Develop AI solutions by using Azure data management services | - Work with Azure data platforms for AI workloads
|
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NEW QUESTION # 45
You are reviewing an Azure Function app that processes incoming order requests for a company. The function must:
* Accept order submissions from an external client application.
* Require controlled access for security
* Return a response containing the processed request payload.
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:
Verified answer: Yes; No; Yes; No.
Detailed Explanation: `auth_level=FUNCTION` means invocation requires a function key unless a stronger platform authentication layer is configured, so the first statement is true. The route explicitly permits POST, not GET. The function reads `req.get_body()` and returns that value in the HttpResponse, so the response contains the request body. No schema, type, required-field, or other payload validation is performed before the response is constructed, making the final statement false.
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 # 46
Case Study 2 - Proseware Inc.
Background
Proseware Inc. develops AI-powered knowledge management solutions for enterprise customers.
The company is modernizing its platform to support semantic search, intelligent document retrieval, and real-time partner integrations.
The engineering team uses Python and Azure SDKs. The architecture is being redesigned to support containerized microservices, vector search workloads, and serverless backend processing.
Planned Application Architecture
Microservices are containerized by using Docker.
Code for containerized microservices and Azure Function apps is developed locally but stored in a GitHub repository.
Custom images for containerized microservices are stored in Azure Container Registry (ACR).
Base images are stored in Docker Hub. Custom images must be rebuilt automatically whenever their base images are updated.
Azure Cosmos DB for NoSQL stores documents, metadata, and vector embeddings.
Azure Functions generate vector embeddings of Azure Cosmos DB for NoSQL-hosted documents and send messages to Service Bus to trigger search index updates.
Azure Container Apps (ACA) apps host backend API services that provide semantic search across Azure Cosmos DB for NoSQL documents. API services process Service Bus messages and update search indexes.
Azure Kubernetes Service (AKS) processes batch vector embedding regeneration for existing Azure Cosmos DB for NoSQL documents (whenever the embedding model is changed).
An extranet-facing containerized webhook allows business partners to submit documents to be processed by internal AI workflows for semantic search and retrieval.
Monitoring
Telemetry generated by Azure resources is sent to Azure Monitor.
A Log Analytics workspace is used to collect ACA apps logs, AKS container logs, and Azure Functions apps logs.
Monitoring of Azure Functions is currently implemented by using Azure Application Insights SDK instrumentation.
Business Requirements
Embeddings for new or updated Azure Cosmos DB for NoSQL-hosted documents must be automatically generated.
Backend API services must scale automatically during business hours.
Cold start delay of backend APIs must be minimized.
Secrets must be stored outside of container images.
Developers must be able to correlate telemetry across Azure Functions hosts and apps.
All tracing must be implemented by using OpenTelemetry SDK instrumentation.
Development efforts must be minimized.
Technical Requirements
Container images must be built automatically and validated before code updates are merged into the main branch.
Image build automation must run inside the Azure Container Registry, eliminating dependency on local developer machines and external build services.
Dependency of image builds on local developer machines must be eliminated.
Event-driven scaling in ACA must occur based on the number of pending messages in the Azure Service Bus queue.
Azure Cosmos DB for NoSQL RU consumption must be minimized.
Vector similarity search must use embeddings stored in Azure Cosmos DB for NoSQL.
The partner-facing containerized webhook service must run on Azure App Service.
Secrets must NOT be stored in container images, source control, or application configuration directly. They must be accessed securely at runtime.
All secrets must be stored centrally in Azure Key Vault and accessed at runtime through a managed identity.
Azure App Service must supply secrets at runtime without relying on external services.
Resources and workloads must be deployed by using Bicep templates through an automated, version-controlled pipeline. Local and command-line deployments must be eliminated to ensure repeatable, auditable deployments.
Known Issues
RU consumption spikes during vector similarity queries.
You need to configure Azure Functions to generate vector embeddings according to planned environment application architecture.
Which trigger type should you use?
Answer: B
Explanation:
The most appropriate trigger type for this architecture is the Azure Cosmos DB Trigger.
This trigger monitors your NoSQL container's underlying change feed. When a document is created or modified, the function fires automatically, processes the data, generates the embedding, and places a message in Azure Service Bus.
Scenario, Planned Application Architecture
Azure Functions generate vector embeddings of Azure Cosmos DB for NoSQL-hosted documents and send messages to Service Bus to trigger search index updates.
Reference:
https://learn.microsoft.com/en-us/azure/cosmos-db/integrated-embeddings
NEW QUESTION # 47
Hotspot Question
You are reviewing an Azure Function app that processes incoming order requests for a company.
The function must
- Accept order submissions from an external client application.
- Require controlled access for security.
- Return a response containing the processed request payload.
You review the following code segment:
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: Yes
Yes, this function requires an API key for invocation.
Authorization Level: The AuthorizationLevel.Function parameter in the trigger dictates the security requirement.
Function Key: You must provide a specific function-level API key to successfully execute the request.
HTTP Status: Accessing this endpoint without a valid key will return a 401 Unauthorized HTTP status code.
How to Pass the Key
You can authenticate your request by passing the key in one of two ways:
Query String: Append ?code=YOUR_FUNCTION_KEY to the end of your request URL.
HTTP Header: Include an x-functions-key header with your key as the value.
Box 2: No
No, this Azure Function does not support HTTP GET requests.
Explicit Method Restriction: The HttpTrigger attribute explicitly defines "post" as the only accepted HTTP method.
Default Behavior Overridden: When you specify methods in the trigger array, all other unlisted methods are blocked.
Box 3: Yes
Yes, this specific Azure Function code segment returns the exact incoming request body back to the caller.
StreamReader(req.Body).ReadToEndAsync(): This line reads the entire raw payload sent in the HTTP POST request and stores it as a string in the result variable.
OkObjectResult(result): This creates an HTTP 200 OK response and places that exact result string directly into the response body.
Box 4: No
No, the provided Azure Function code does not validate the request body before returning a response.
Direct Echo: The function reads the raw request stream into a string variable named result.
Immediate Return: It instantly passes that unverified string directly into an OkObjectResult.
Missing Logic: There are no schema checks, null checks, type validations, or business logic evaluations performed on the data.
Reference:
https://learn.microsoft.com/en-us/azure/durable-task/durable-functions/durable-functions-http-api
NEW QUESTION # 48
You are reviewing an Azure Function app that processes incoming order requests for a company. The function must:
* Accept order submissions from an external client application.
* Require controlled access for security
* Return a response containing the processed request payload.
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:
Verified Answer: Yes; No; Yes; No.
Detailed Explanation: `auth_level=FUNCTION` means invocation requires a function key unless a stronger platform authentication layer is configured, so the first statement is true. The route explicitly permits POST, not GET. The function reads `req.get_body()` and returns that value in the HttpResponse, so the response contains the request body. No schema, type, required-field, or other payload validation is performed before the response is constructed, making the final statement false.
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 # 49
You need to configure image build automation based on the technical requirements.
Which settings should you configure? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
* Trigger for container images build: Base image update
* Implementation of image builds: ACR Task
The correct trigger is Base image update because Proseware requires every custom container image to be rebuilt automatically whenever its Docker Hub base image changes. Azure Container Registry Tasks can detect base-image dependencies from the Dockerfile FROM instruction and automatically trigger a rebuild when that base image is updated. Microsoft confirms that ACR Tasks can track base images in public repositories such as Docker Hub and Microsoft Container Registry, as well as images stored in Azure Container Registry.
The build implementation must be an ACR Task . This directly satisfies the technical requirement that image- build automation run inside Azure Container Registry , eliminating dependencies on local developer machines or separate external build services. ACR Tasks provides cloud-based container building and can automate builds based on source-code commits, base-image updates, or scheduled triggers.
A GitHub workflow could orchestrate CI/CD, but using it as the actual image-building implementation would conflict with the explicit requirement that builds execute inside ACR. Docker Compose defines multi- container applications; it is not the native ACR build automation mechanism. A Commit trigger addresses source changes rather than the stated base-image update requirement, while Scheduled builds would introduce unnecessary periodic execution.
Study Guide references: Azure Container Registry Tasks; base-image dependency tracking; automated rebuilds; Docker Hub base-image triggers; cloud-native container builds.
NEW QUESTION # 50
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