AI-200 Security And Observability Practice Test 8 — 15 Questions

Question 1

You need to secure an Azure Machine Learning workspace against data exfiltration. Which THREE configurations should you implement?

Accepted Answer

Disable public network access on the Azure Machine Learning workspace.. Option A is correct because disabling public network access on the Azure Machine Learning workspace forces all client and service traffic through private endpoints or approved private paths, eliminating the public internet as an exfiltration route. Option D is correct because a workspace managed virtual network isolates compute and uses approved outbound rules (via private endpoints or FQDNs), preventing compute from sending data to unapproved external destinations. Option E is correct because private endpoints for dependent services such as Azure Storage, Key Vault, and Azure Container Registry keep that traffic on the Microsoft backbone/private IP space, so data cannot be exfiltrated through those services' public endpoints. Option B is incorrect because granting Contributor at subscription scope broadens access and violates least privilege rather than securing against exfiltration. Option C is incorrect because attaching public IP addresses to compute instances exposes them to inbound/outbound internet traffic and increases exfiltration risk.

Answer

Assign the Contributor role to all users on the subscription level.

Answer

Attach public IP addresses to all compute instances for rapid troubleshooting.

Question 2

You are deploying an Azure OpenAI Service resource and must ensure that all traffic from your virtual network reaches the endpoint without traversing the public internet. Which feature should you configure?

Accepted Answer

Configure a Private Endpoint for the Azure OpenAI resource. Private endpoints use private IP addresses from your VNet to securely bring services into your VNet, eliminating public exposure.

Answer

Enable public network access with selected IP address ranges

Answer

Configure a Service Endpoint without enabling virtual network rules

Answer

Deploy an Azure Application Gateway in front of the endpoint

Question 3

Which THREE logs or telemetry types should you collect in Azure Monitor to comprehensively troubleshoot an AI-powered web application?

Accepted Answer

Application requests and response status codes.. Application Insights collects request telemetry, dependency tracking for API calls, and trace logs for debugging logic.

Answer

Azure Bastion audit logs.

Answer

Azure Firewall packet capture PCAP files.

Question 4

Your development team needs to store API keys and connection strings for an Azure Cognitive Search service securely without embedding them in the source code. Where should you store these secrets?

Accepted Answer

Azure Key Vault. Azure Key Vault is the dedicated Azure service for storing and tightly controlling access to secrets, keys, and certificates. Storing API keys and connection strings there keeps them out of source code and enables RBAC, auditing, and managed identity access.

Answer

An Azure Storage Table with public read permissions

Answer

An environment variable in the application's appsettings.json file

Answer

The Azure AI Studio model deployment configuration metadata

Question 5

You are configuring role-based access control for an Azure AI Search service. A data scientist needs to index content and query documents, but must not be permitted to manage service-level keys or change admin configurations. Which built-in role should you assign?

Accepted Answer

Search Index Data Contributor. Search Index Data Contributor grants data-plane rights to read and write documents in indexes and to query them, which is exactly what a data scientist needs. It does not include the control-plane permissions to manage service keys, scale the service, or change admin configuration. That separation of duties matches the stated requirement.

Answer

Search Service Contributor

Answer

Cognitive Services Contributor

Answer

Storage Blob Data Reader

Question 6

An enterprise application calls multiple Azure AI Language services. You need to trace requests across multiple distributed microservices to diagnose high latency issues. Which Azure Monitor capability should you implement?

Accepted Answer

Application Insights Distributed Tracing. Distributed tracing in Application Insights tracks requests across multiple service boundaries using W3C Trace Context headers.

Answer

Azure Advisor cost recommendations

Answer

Log Analytics metric alerts without instrumentation

Answer

Azure Network Watcher Connection Monitor

Question 7

Your team is using managed identities to connect an Azure App Service web app to an Azure OpenAI resource. The connection fails with a 403 Forbidden error. What is the most likely root cause?

Accepted Answer

The managed identity has not been granted the 'Cognitive Services OpenAI User' role on the Azure OpenAI resource.. A 403 Forbidden from Azure OpenAI when using a managed identity almost always means the identity authenticated successfully (otherwise you'd see 401) but lacks the required data-plane RBAC role. The 'Cognitive Services OpenAI User' role grants the necessary permissions to call the Azure OpenAI inference endpoints. Assigning this role to the App Service's managed identity on the Azure OpenAI resource resolves the 403.

Answer

The App Service must be bound to a custom domain before managed identities can issue bearer tokens.

Answer

The app service requires a client secret stored in Azure Key Vault for managed identity authentication.

Answer

System-assigned managed identities cannot authenticate against Azure AI PaaS endpoints.

Question 8

You need to monitor the monthly spending on Azure OpenAI token consumption and receive an alert when expenditures exceed a predefined threshold. Which tool should you use?

Accepted Answer

Azure Cost Management Budgets and Alerts. Azure Budgets in Cost Management allow you to set spending thresholds and automated email alerts when thresholds are reached.

Answer

Log Analytics Workspace usage and estimated costs view

Answer

Application Insights availability tests

Answer

Azure Security Center compliance dashboard

Question 9

You are troubleshooting intermittent HTTP 429 (Too Many Requests) errors from an Azure OpenAI deployment. Which metric in Azure Monitor should you inspect to confirm whether token rate limits are being exceeded?

Accepted Answer

Normalized Token Utilization. Normalized Token Utilization is the Azure OpenAI metric that expresses consumed tokens as a percentage of the deployment's tokens-per-minute (TPM) quota. When it approaches or exceeds 100%, the service returns HTTP 429, so this metric directly confirms whether rate limits are the cause.

Answer

System Assigned Managed Identity Success Rate

Answer

Virtual Network Gateway Packet Drops

Answer

Data Ingestion Volume (GB)

Question 10

Your company policy requires securing AI model endpoints by disabling public internet access and ensuring all API requests use secure managed identities. Which TWO actions must you take? (Choose two)

Accepted Answer

Disable public network access on the Azure AI service resource and configure a private endpoint.. Option A is correct because disabling public network access on the Azure AI service resource and configuring a private endpoint ensures the endpoint is reachable only through a private IP address inside the virtual network, satisfying the requirement to remove public internet exposure. Option E is correct because assigning the appropriate Azure RBAC role (for example, Cognitive Services User or equivalent) to the application's managed identity on the AI service enables token-based, keyless authentication via Microsoft Entra ID, which is exactly how secure managed identities are used for API requests. Option B is wrong because an unencrypted HTTP binding violates the security requirement and offers no managed identity authentication. Option C is wrong because storing model weights and endpoint keys in public GitHub repositories exposes secrets and is a severe security violation. Option D is wrong because a long-lived SAS token is a shared secret credential, not a managed identity, and a 10-year expiration creates an unacceptable security risk.

Answer

Expose the AI endpoint via an unencrypted HTTP binding for maximum performance.

Answer

Store all AI model weights and endpoint keys in public GitHub repositories for CI/CD access.

Answer

Configure a shared access signature (SAS) token with a 10-year expiration period.

Question 11

You are configuring comprehensive observability for an intelligent application built on Azure AI Document Intelligence and Azure OpenAI. Which THREE telemetry types or tools should you configure in Application Insights to capture complete operational insights? (Choose three)

Accepted Answer

Configure dependency tracking to monitor outgoing HTTP calls made to Azure AI REST endpoints.. Option A is correct because Application Insights dependency tracking automatically captures outgoing HTTP/REST calls to Azure AI Document Intelligence and Azure OpenAI endpoints, recording duration, result codes, and failures so you can diagnose latency and errors in the AI service calls. Option B is correct because custom events let you log domain-specific telemetry such as document processing success rates, which are not captured by default request/dependency metrics and are essential for business-level observability. Option D is correct because exception telemetry automatically captures unhandled runtime errors with stack traces, enabling root-cause analysis of failures in the application code. Option C is incorrect because Azure Firewall policy management is a networking security function and cannot be installed into the Application Insights SDK. Option E is incorrect because Microsoft Entra ID conditional access policies govern authentication/authorization and cannot restart unhealthy worker threads.

Answer

Install the Azure Firewall policy manager directly onto the Application Insights SDK.

Answer

Use Azure Active Directory conditional access policies to restart unhealthy worker threads.

Question 12

You are configuring an Azure OpenAI service instance. You need to ensure that the service is only accessible from your corporate virtual network and that public internet access is completely disabled. Which configuration should you implement?

Accepted Answer

Create a Private Endpoint, disable public network access in the Networking tab, and verify the DNS zone configuration.. To make an Azure OpenAI instance reachable only from a corporate VNet with no public internet access, you must create a Private Endpoint (which assigns a private IP from your VNet to the service), disable public network access on the Networking tab, and ensure the private DNS zone (privatelink.openai.azure.com) is linked so name resolution returns the private IP. All three steps are required for a fully private, functional deployment.

Answer

Set the firewall rules to block all traffic and allow only the specific IP address of your NAT gateway.

Answer

Configure a Service Tag in the Network Security Group to allow only specific IP ranges.

Answer

Implement Azure AD Conditional Access policies to restrict access based on user location.

Question 13

To optimize costs and monitor consumption for an Azure OpenAI deployment across multiple business units, which THREE practices should you implement? (Choose three)

Accepted Answer

Apply Azure resource tags representing cost centers or business units to all AI service instances.. Option A is correct because applying Azure resource tags that represent cost centers or business units to every AI service instance enables cost allocation and chargeback reporting in Azure Cost Management, which is essential for tracking consumption per business unit. Option C is correct because Azure Monitor exposes token usage metrics for Azure OpenAI, and analyzing those patterns lets you decide whether Provisioned Throughput Units (PTUs) or Pay-As-You-Go token billing is cheaper for each workload's utilization profile. Option E is correct because Azure Budgets support alert actions (email, action groups, automation) that notify department heads when actual or forecasted spend reaches a threshold such as 80% of allocation, enabling proactive cost control. Option B is wrong because deleting Log Analytics diagnostic logs immediately destroys the telemetry needed for monitoring and auditing, and diagnostic logs are not the primary driver of Azure OpenAI cost. Option D is wrong because permanently provisioning maximum PTUs regardless of active workload wastes money, since PTUs are billed hourly whether or not they are used.

Answer

Delete all Log Analytics diagnostic logs immediately upon generation to reduce storage billing.

Answer

Provision maximum possible provisioned throughput units permanently regardless of active workload.

Question 14

Your team has noticed a significant cost spike in your Azure OpenAI usage. You need to identify which specific deployment is responsible for the highest token consumption. Which tool provides the most granular visibility into this data?

Accepted Answer

Azure Monitor metrics with splitting on the 'DeploymentName' dimension.. Azure Monitor platform metrics for Azure OpenAI expose a 'DeploymentName' dimension on metrics such as TokenTransaction, ProcessedPromptTokens, and GeneratedCompletionTokens. Splitting on that dimension gives per-deployment token consumption, which is the most granular native view for attributing cost to a specific deployment.

Answer

Azure Advisor cost recommendations.

Answer

Application Insights logs via KQL query on the 'requests' table.

Answer

Azure Cost Management analysis on the resource group.

Question 15

An Azure Machine Learning model is deployed to a Kubernetes cluster. Users report intermittent 503 errors. You suspect the underlying compute nodes are overloaded. Where should you look first to correlate these errors with infrastructure health?

Accepted Answer

Container Insights in Azure Monitor.. Container Insights (part of Azure Monitor) provides integrated monitoring for AKS, allowing you to correlate pod restarts and node resource exhaustion with application errors.

Answer

Azure Key Vault audit logs.

Answer

Log Analytics Workspace 'AppRequests' table.

Answer

Azure Machine Learning studio 'Endpoints' monitoring tab.