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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Secure, monitor, and optimize AI solutions | 20% | - Manage security and configuration
|
| Topic 2: Integrate backend services and build event-driven architectures | 25% | - Build serverless APIs and workflows
|
| Topic 3: Develop containerized AI solutions on Azure | 25% | - Monitor and troubleshoot containerized workloads
|
| Topic 4: Develop AI solutions using Azure data services | 30% | - Design and optimize data access and retrieval
|
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NEW QUESTION # 93
Hotspot Question
You are developing several microservices to run on Azure Container Apps. External HTTP ingress traffic has been enabled for the microservices.
A deployed microservice must be updated to allow users to test new features. You have the following requirements:
- Enable and maintain a single URL for the updated microservice to
provide to test users.
- Update the microservice that corresponds to the current microservice
version.
You need to configure Azure Container Apps.
Which features should you configure? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Revision label
You should use the revision labels feature in Azure Container Apps. This feature allows you to assign a dedicated, permanent URL to a specific version (or revision) of your microservice.
Box 2: Revision mode
The application's Revision mode must be configured to Multiple. This allows the existing (current) microservice version to remain active and serve production traffic concurrently while you spin up the updated revision for the test users to access safely.
Reference:
https://learn.microsoft.com/en-us/azure/container-apps/microservices
NEW QUESTION # 94
Drag and Drop Question
You are designing Azure Functions for three different backend workloads.
Each workload requires one of the following dispatching models:
- Return an immediate response to a client.
- Process background work from a queue.
- Run code on a fixed schedule.
You need to select the trigger for each requirement.
Which triggers should you select? To answer, move the appropriate triggers to the correct requirements. You may use each trigger 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: HTTP trigger
An HTTP trigger is the best choice for returning an immediate response to a client.
Direct connection: The client makes a standard web request and waits on the same connection.
Low latency: It avoids the delays introduced by routing messages through queues or storage.
Two-way communication: It natively supports returning payload data and HTTP status codes (e.g., 200 OK).
Box 2: Queue Storage Trigger
Azure Queue Storage Trigger or Azure Service Bus Queue Trigger is the best choice to process background work from a queue.
Azure Queue Storage Trigger:
Best for simple, low-cost message queues with high throughput and straightforward FIFO (first-in, first-out) processing needs.
Automatic Scaling: Scales out instances dynamically based on the number of messages waiting in the queue.
Reliability: Automatically handles poison messages and retries failed executions if configured correctly.
Cost Efficiency: Consumes zero compute resources when the queue is empty (especially under the Consumption plan).
Box 3: Timer trigger
An Azure Function with a timer trigger is the standard and ideal choice for running code on a fixed schedule. It acts as a serverless cron job that automatically manages execution intervals, scales automatically, and includes built-in locking mechanisms to prevent duplicate executions across multiple instances.
Reference:
https://levelup.gitconnected.com/request-driven-service-vs-event-driven-service-4bf04d642843?gi=c0bdcb16db5a
https://codilime.com/blog/enabling-first-in-first-out-pattern-microsoft-azure-service-bus-queues-topics/
NEW QUESTION # 95
You must ensure that PII (personally identifiable information) such as names and phone numbers is automatically redacted from support ticket transcripts before they are stored. What should you use?
Answer: D
Explanation:
Azure AI Language's PII detection feature identifies and can redact categories of sensitive information (names, phone numbers, SSNs, etc.) from unstructured text, which is the purpose- built service for this scenario.
NEW QUESTION # 96
You are developing an Azure Functions app.
All functions in the app meet the following requirements:
Run until either a successful run or until 10 run attempts occur.
Ensure that there are at least 20 seconds between attempts for up to 15 minutes.
You need to configure the host.json file.
How should you complete the code segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
NEW QUESTION # 97
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. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear on the review screen.
You plan to deploy a container to an Azure App Service API app named api1. You host the source code for api1 in a GitHub repository. The container uses the API key at runtime to connect to a backend service.
The container must be able to retrieve the API key at runtime without exposing it in the source repository or Git commit history.
You need to ensure that the API key remains outside of Git commit history and is available to the container at runtime.
Solution: Embed the API key as a hardcoded environment variable in the Dockerfile.
Does the solution meet the goal?
Answer: B
Explanation:
Correct:
* Store the API key in Azure Key Vault and reference it from an App Service application setting.
Storing the API key in Azure Key Vault and referencing it via App Service application settings is the recommended, secure approach. This strategy completely removes sensitive credentials from your GitHub repository and Git commit history while injecting them safely into your container environment at runtime.
Incorrect:
* Embed the API key as a hardcoded environment variable in the Dockerfile.
* Store the API key as a GitHub repository secret.
Reference:
https://www.qservicesit.com/full-stack-applications-on-azure
NEW QUESTION # 98
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