AI-103 Plan And Manage AN Azure AI Solution Practice Test 8 — 15 Questions

Question 1

You are monitoring the performance of a deployed Azure OpenAI model. You notice occasional HTTP 429 (Too Many Requests) errors occurring during peak traffic hours. Which monitoring and management action should you take to resolve this issue?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Configure Azure Monitor metric alerts for 'Token Generation Rate' and scale up your provisioned throughput deployment capacity.. HTTP 429 errors indicate that you have exceeded the rate limits (Tokens Per Minute or Requests Per Minute) of your provisioned tier. Upgrading to a Provisioned Throughput deployment or implementing exponential backoff retry logic resolves rate-limiting errors.

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Disable content safety filters to reduce processing latency and throughput overhead.

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Rotate the primary API key immediately to clear the server-side connection cache.

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Update the Network Security Group rules to increase the maximum allowed packet size for the API endpoint.

Question 2

You need to provision an Azure AI resource that allows developers to access multiple AI capabilities (such as Vision, Speech, and Language) using a single endpoint and a single API key. Which resource type should you create?

Accepted Answer

Azure AI multi-service account. An Azure AI multi-service resource allows you to integrate Vision, Speech, Language, and other services using a single key and endpoint. Single-service resources require separate keys and endpoints for each service.

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Azure Cognitive Search resource

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Azure OpenAI resource

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Azure AI Custom Vision resource

Question 3

Your organization has strict compliance policies requiring all Azure AI Services endpoints to reject connections that do not use Transport Layer Security (TLS) version 1.3. Where can you enforce this minimum TLS version setting?

Accepted Answer

In the Configuration blade of the Azure AI resource in the Azure Portal. The minimum TLS version for Azure AI Services can be enforced globally on the resource via the 'Configuration' blade in the Azure Portal or using Azure Policy. IAM, diagnostic settings, and Application Insights do not configure TLS versions.

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Within the Data residency tab of the Overview blade

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In the Access control (IAM) settings under role assignments

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In Application Insights under the Availability blade

Question 4

Your enterprise architecture team is reviewing the security posture of an Azure AI deployment that handles sensitive financial documents. Which TWO actions should you implement to secure data in transit and at rest? (Choose two.)

Accepted Answer

Enforce a minimum TLS version of 1.2 or higher for all API requests to secure data in transit.. Customer-managed keys (CMK) via Azure Key Vault protect data at rest, and enforcing TLS 1.2 or TLS 1.3 secures data in transit. Disabling diagnostics, using standard keys, or disabling RBAC reduces security.

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Grant 'Contributor' permissions to all developer accounts to simplify key rotation.

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Disable diagnostic logging to prevent sensitive document text from being stored in Log Analytics.

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Use Microsoft-managed keys exclusively without integrating Azure Key Vault.

Question 5

When planning an Azure AI solution deployment strategy, what are THREE key considerations for model versioning and lifecycle management? (Choose three.)

Accepted Answer

Implementing automated regression testing in CI/CD pipelines when upgrading model versions.. Model updates require planning around version deprecation notices, validating output consistency, and testing rollback strategies. Relying on auto-updates without testing can break downstream integrations.

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Deleting older model versions immediately upon release of a new version to save cloud storage costs.

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Hardcoding the latest model version string into production code without version specifiers.

Question 6

You are troubleshooting an intermittent connectivity issue between a client application and an Azure AI Speech service that sits behind an Azure Firewall and a Virtual Network. Which THREE diagnostic steps or tools should you utilize? (Choose three.)

Accepted Answer

Use Azure Network Watcher IP Flow Verify to check if traffic is being blocked by network security groups.. Network Watcher IP Flow Verify, NSG flow logs, and Diagnostic settings (enabling logs and metrics) are core tools for troubleshooting network routing and service errors. ARM template visualizers and Azure Advisor cost recommendations do not diagnose network connectivity issues.

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Run the Azure Advisor cost recommendation analyzer to optimize resource pricing tiers.

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Use the Azure Resource Manager template visualizer to inspect regional resource dependencies.

Question 7

You need to ensure that an Azure AI services resource is accessible only from a specific virtual network. Which configuration should you update in the Azure portal?

Accepted Answer

The Networking blade to configure Private endpoints.. Private endpoints provide secure, private access to Azure AI services via a private IP address within your VNET.

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The Resource tags to add a network security group.

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The Authentication blade to disable local keys.

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The Identity blade to assign a User Assigned Managed Identity.

Question 8

You are deploying a custom model to an Azure AI managed endpoint. You need to ensure the deployment can access a Key Vault secret without storing credentials in the deployment configuration. What should you do?

Accepted Answer

Assign a User-assigned managed identity to the endpoint and grant it Key Vault Secrets User access.. Using a User-assigned managed identity allows the endpoint to authenticate to other Azure services like Key Vault securely.

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Enable public access on the Key Vault and use an IP firewall rule.

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Inject the secret directly into the environment variables during deployment.

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Configure a System-assigned identity on the endpoint and grant it Key Vault Reader access.

Question 9

You are managing costs for a multi-tenant Azure AI project. You need to attribute usage costs specifically to the 'Research' department. What is the most effective approach?

Accepted Answer

Implement Azure Policy to enforce mandatory tags on all new resources.. Tags are key-value pairs that help organize and track costs in Azure Cost Management.

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Disable diagnostic logging for the research resources to reduce billing.

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Create a separate resource group for each department.

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Change the pricing tier of the resource to 'Free'.

Question 10

You have an Azure AI Search service. You need to monitor the number of failed queries to identify potential indexing issues. Which tool should you use?

Accepted Answer

The 'Metrics' blade in the Azure portal for the Search service.. Azure Monitor metrics are the standard way to track service health and query performance.

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The 'Activity Log' in the Subscription blade.

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The 'Security Center' recommendation dashboard.

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The 'Resource Health' blade.

Question 11

A company requires that all AI models be approved by a compliance officer before they are deployed to production. Which feature facilitates this workflow?

Accepted Answer

Azure AI Model Registry versioning and tagging.. Azure AI Model Catalog and Registry allow for lineage and approval tracking in enterprise environments.

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Azure Service Bus queues.

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Blob Storage access policies.

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Azure Function webhooks.

Question 12

Which authentication method is recommended to prevent 'key leakage' in Azure AI Services?

Accepted Answer

Using Microsoft Entra ID authentication.. Microsoft Entra ID (formerly Azure AD) provides role-based access control without needing to rotate or manage static subscription keys.

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Storing keys in a plaintext file.

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Creating custom headers for API requests.

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Regenerating keys every 30 days.

Question 13

You are deploying a model that requires significant GPU resources. You want to ensure the deployment only scales when the average CPU load exceeds 70%. Which feature of Azure AI managed endpoints do you configure?

Accepted Answer

The 'Endpoints' deployment configuration 'autoscaling' settings.. Autoscaling settings on Azure AI managed endpoints allow you to define rules based on resource utilization metrics like CPU or GPU load.

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The 'Load Balancer' settings in the VNET.

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Azure Front Door health probe settings.

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The 'Compute' instance restart policy.

Question 14

You need to view the latency of requests made to an Azure AI services endpoint. Where do you find this information?

Accepted Answer

Azure Monitor metrics.. Azure Monitor metrics provide granular detail on latency and request rates for AI services.

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The Subscription billing dashboard.

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The 'Deployment' logs in the machine learning workspace.

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Azure Advisor recommendations.

Question 15

You have an Azure AI application that is hitting rate limits (429 errors). You need to determine which specific client application is causing the issue. How do you identify this?

Accepted Answer

Enable diagnostic logging to Log Analytics and run a KQL query.. Diagnostic logs (sent to Log Analytics) can be configured to include client-side metadata or IP information for request tracing.

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Check the 'Activity Log'.

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Increase the resource quota in the 'Quotas' blade.

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Restart the AI service.