AI-103 Plan And Manage AN Azure AI Solution Practice Test 9 — 15 Questions

Question 1

Which Azure feature allows you to control which users can modify or delete your Azure AI resources?

Accepted Answer

Azure RBAC.. Azure RBAC (Role-Based Access Control) manages fine-grained permissions for users on Azure resources.

Answer

Conditional Access policies.

Answer

Azure Firewall.

Answer

Resource Locks.

Question 2

You are migrating an Azure AI service from one region to another. What is the most efficient way to migrate the configuration?

Accepted Answer

Export the resource as an ARM template and deploy it to the new region.. Azure Resource Manager (ARM) templates or Bicep files are the standard for infrastructure as code, ensuring consistent replication.

Answer

Restore a backup from a Recovery Services vault.

Answer

Use Azure Data Factory to copy the resource.

Answer

Manually recreate all resources in the new region.

Question 3

What is the purpose of a 'Resource Group' in the context of Azure AI solutions?

Accepted Answer

To act as a logical container for managing related resources.. Resource groups act as a logical container for related Azure resources, making it easier to manage the lifecycle, permissions, and billing of a solution.

Answer

To provide high availability for the service.

Answer

To enforce network firewall rules.

Answer

To store the model weights.

Question 4

You need to ensure that an AI model deployment is resilient to regional outages. What should you implement?

Accepted Answer

Azure Front Door with regional endpoints.. Global load balancing using services like Azure Front Door or Traffic Manager allows for failover across regions.

Answer

A single large VM.

Answer

Azure Storage redundancy.

Answer

Local VNET peering.

Question 5

When setting up an Azure AI service, you choose the 'Standard' tier. What is the primary benefit of this compared to the 'Free' tier?

Accepted Answer

Higher rate limits and production-level SLAs.. Standard tiers provide higher capacity, production-level SLAs, and support for enterprise-grade features.

Answer

Lower latency for all requests.

Answer

Access to experimental AI models.

Answer

Automatic data encryption.

Question 6

You have an Azure AI endpoint exposed to the internet. You want to ensure traffic is inspected for malicious patterns. What is the recommended service?

Accepted Answer

Azure Web Application Firewall (WAF).. Azure Web Application Firewall (WAF) provides protection against common web vulnerabilities like SQL injection and cross-site scripting.

Answer

Network Security Group (NSG) rules.

Answer

Azure Bastion.

Answer

Azure AI Content Safety.

Question 7

You are using an Azure AI model that supports versioning. You want to perform an A/B test by routing 10% of traffic to a new version. Where do you configure this?

Accepted Answer

The 'Traffic' configuration in the Azure AI endpoint.. In Azure AI managed endpoints, you can define traffic distribution across multiple deployments within the same endpoint.

Answer

Azure App Service routing rules.

Answer

Azure Load Balancer backend pools.

Answer

Azure Traffic Manager DNS settings.

Question 8

Which command line tool is primarily used for managing Azure resources, including AI services, from a terminal?

Accepted Answer

Azure CLI.. The Azure CLI (az) is the standard command-line interface for managing Azure resources.

Answer

Azure PowerShell.

Answer

Docker.

Answer

Kubectl.

Question 9

What is the purpose of 'Azure Advisor' in an AI solution?

Accepted Answer

To provide best practice recommendations for resources.. Azure Advisor provides personalized recommendations for cost optimization, security, reliability, and performance.

Answer

To manage user identities.

Answer

To automatically patch the AI models.

Answer

To host the web frontend for the AI application.

Question 10

Which TWO actions should you take to ensure that your Azure AI deployment is secure?

Accepted Answer

Use Managed Identities for service-to-service communication.. Enforcing TLS 1.2+ and using managed identities are standard security best practices for Azure AI.

Answer

Keep the public IP exposed at all times.

Answer

Store all keys in a public GitHub repository.

Answer

Use the default 'Owner' role for all users.

Question 11

You are deploying a custom AI model using a container image stored in Azure Container Registry (ACR). How do you ensure the deployment can pull the image securely?

Accepted Answer

Assign the 'AcrPull' role to the endpoint's managed identity.. Granting the AI service's managed identity the 'AcrPull' role on the registry allows it to pull images securely without shared secrets.

Answer

Use the ACR 'admin' password in the configuration.

Answer

Deploy the model from a local machine.

Answer

Make the ACR public.

Question 12

You need to export logs from your Azure AI service to an external SIEM (Security Information and Event Management) system. What is the best way to achieve this?

Accepted Answer

Configure a diagnostic setting to stream logs to an Event Hub.. Azure Monitor diagnostic settings allow you to stream logs to an Event Hub, which is a common integration point for third-party SIEMs.

Answer

Copy the files manually from Blob Storage.

Answer

Use an Azure Logic App to poll the REST API.

Answer

Enable public access on the log file store.

Question 13

Your team needs to receive an email alert if the error rate for your AI endpoint exceeds 5% for more than 15 minutes. What should you create?

Accepted Answer

An Azure Monitor Alert rule with an Action Group.. Azure Monitor Alert rules allow you to trigger actions (like email notifications via action groups) based on metric thresholds.

Answer

An Azure Service Health notification.

Answer

A scheduled Azure Function that polls the API.

Answer

A Log Analytics query saved as a report.

Question 14

Which THREE features are critical for managing the lifecycle of an AI model in a production environment?

Accepted Answer

Model registry for version control.. Versioning, monitoring, and automated deployment pipelines are essential for production AI lifecycle management.

Answer

Hardcoding all environment settings.

Answer

Manual file copying via FTP.

Question 15

Which TWO monitoring strategies are effective for detecting 'data drift' in a deployed AI model?

Accepted Answer

Tracking changes in input data distribution.. Monitoring input data distributions and model performance metrics are the two primary ways to detect drift.

Answer

Checking the physical temperature of the CPU.

Answer

Monitoring total API request volume.

Answer

Restarting the endpoint every hour.