AI-102 Plan and manage an Azure AI solution Practice Test 4 — 15 Questions

Question 1

You are deploying a custom question-answering solution using Azure AI Language. The solution must support multiple languages and provide answers from a set of FAQ documents. You need to ensure that the service can handle up to 1000 requests per minute with low latency. What should you configure?

Accepted Answer

Use the Standard tier and allocate 10 capacity units (CUs).. Option B is correct because Azure AI Language's custom question-answering feature uses a Standard tier with capacity units (CUs) to handle throughput and latency. Each CU provides a baseline of 100 requests per minute (RPM), so 10 CUs deliver exactly 1000 RPM, meeting the requirement. The Standard tier also supports multiple languages and low-latency responses from FAQ documents.

Answer

Use Azure AI Search with a basic tier and replicas.

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Use the Free tier and enable autoscaling.

Answer

Deploy a dedicated endpoint with provisioned throughput of 1000 TPS.

Question 2

You are designing a responsible AI solution for a healthcare application that uses Azure AI Vision to analyze medical images. The solution must minimize bias across demographic groups and provide explainability for predictions. Which combination of services should you use?

Accepted Answer

Azure AI Content Safety for content moderation and Fairlearn with Azure Machine Learning interpretability.. Option D is correct because Azure AI Content Safety helps filter harmful content and reduce bias in model outputs, while Fairlearn with Azure Machine Learning interpretability provides tools to assess fairness across demographic groups and explain model predictions. This combination directly addresses the requirements of minimizing bias and providing explainability for medical image analysis.

Answer

Azure AI Document Intelligence for extracting metadata and Azure AI Language for sentiment analysis.

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Azure AI Translator for multilingual support and Azure AI Metrics Advisor for monitoring.

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Azure AI Search for indexing results and Azure AI Anomaly Detector for outliers.

Question 3

Your company uses Azure OpenAI Service to generate marketing content. You need to ensure that the generated content does not contain offensive language. Which feature should you enable?

Accepted Answer

Azure AI Content Safety filters.. Azure AI Content Safety filters are specifically designed to detect and block offensive, inappropriate, or harmful language in text and images. By enabling these filters on your Azure OpenAI Service deployment, you can configure severity thresholds for categories like hate, self-harm, sexual, and violence content, ensuring generated marketing content meets safety policies.

Answer

Audit logging for all API calls.

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Data encryption at rest.

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Rate limiting on the endpoint.

Question 4

You are deploying an Azure AI Search solution for a global e-commerce platform. The index must support real-time updates from a product catalog stored in Azure Cosmos DB, with a maximum indexing latency of 10 seconds. The solution must also handle 5000 queries per second (QPS) during peak hours. What should you configure?

Accepted Answer

Use Standard S3 tier with 12 replicas and enable incremental indexing.. Option C is correct because the Standard S3 tier supports high query volumes (up to 5000 QPS) with 12 replicas, and incremental indexing enables near-real-time updates from Cosmos DB by processing only changed documents, keeping latency under 10 seconds. The combination of sufficient replicas for throughput and incremental indexing for low-latency indexing meets both requirements.

Answer

Use the Storage Optimized L2 tier with 6 partitions and 4 replicas.

Answer

Use the Free tier and enable change tracking on Cosmos DB.

Answer

Use Standard S2 tier with 3 replicas and indexer scheduling every 5 minutes.

Question 5

Which TWO actions should you take to ensure compliance with data privacy regulations when using Azure AI Language to process customer support transcripts that contain personally identifiable information (PII)?

Accepted Answer

Enable PII detection and redaction in the Azure AI Language service.. Option D is correct because Azure AI Language's PII detection and redaction feature is specifically designed to identify and mask personally identifiable information (PII) in text, such as names, addresses, and social security numbers, directly within the service. This built-in capability ensures that sensitive data is removed or obfuscated before storage or further processing, directly supporting compliance with data privacy regulations like GDPR or HIPAA.

Answer

Disable diagnostic logging for the resource.

Answer

Use customer-managed keys (CMK) for encryption.

Answer

Apply Azure AI Content Safety filters to anonymize personal data.

Question 6

Which THREE considerations are essential when designing a cost management strategy for an enterprise Azure AI solution that uses multiple AI services, including Azure OpenAI Service, Azure AI Language, and Azure AI Vision?

Accepted Answer

Choose provisioned throughput units (PTUs) for Azure OpenAI Service for predictable workloads.. Option B is correct because provisioned throughput units (PTUs) for Azure OpenAI Service provide reserved capacity, ensuring predictable performance and cost for stable workloads. PTUs are ideal for enterprise scenarios where latency and throughput must be consistent, as they allocate dedicated model processing capacity and avoid pay-per-token variability.

Answer

Use the Free tier for all services to minimize upfront costs.

Answer

Deploy Azure Site Recovery to replicate AI services across regions.

Question 7

Which TWO monitoring metrics should you track to ensure the health and performance of an Azure AI Search service used for a customer-facing product catalog?

Accepted Answer

Throttled search queries count.. Throttled search queries count (Option A) is a critical health metric because it directly indicates when the search service is under excessive load, causing requests to be rate-limited. For a customer-facing product catalog, throttling degrades user experience and can lead to failed searches. Tracking this metric helps you decide when to scale up replicas or partitions to maintain service level agreements.

Answer

Indexer execution history and duration.

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Storage used in GB.

Answer

Number of successful search requests.

Question 8

You are developing a chatbot using Azure AI Bot Service that uses Azure OpenAI Service for natural language understanding. The chatbot must be deployed in multiple regions for low latency. However, the customer requires that all customer data remain within the European Union. Which architecture should you recommend?

Accepted Answer

Deploy the bot and all supporting services in multiple EU regions, e.g., West Europe and North Europe, without cross-region data replication.. Option C is correct because deploying the bot and all supporting services in multiple EU regions (e.g., West Europe and North Europe) ensures low latency for users across Europe while keeping all customer data within the European Union. Azure OpenAI Service and Azure AI Bot Service can be deployed regionally without cross-region data replication, satisfying the data residency requirement. This architecture avoids any data leaving EU boundaries while providing geographic redundancy for performance.

Answer

Deploy the bot in a single EU region and rely on CDN for static content.

Answer

Use Azure Front Door to route traffic to a single bot hosted in West Europe.

Answer

Deploy the bot in multiple global regions and use Cosmos DB with multi-region writes.

Question 9

Your organization uses Azure AI Document Intelligence to extract data from invoices. The solution must identify custom fields not present in the prebuilt models, such as 'purchase order number' located in varying positions across documents. What should you do?

Accepted Answer

Train a custom extraction model using labeled sample invoices.. Option D is correct because Azure AI Document Intelligence (formerly Form Recognizer) allows you to train a custom extraction model using labeled sample invoices. This approach enables the model to learn custom fields like 'purchase order number' that appear in varying positions, which prebuilt models cannot handle. By providing labeled examples, the model generalizes to extract the field accurately from new documents.

Answer

Use the layout model and apply manual post-processing.

Answer

Use Azure AI Forms Recognizer with prebuilt receipt model.

Answer

Use the prebuilt invoice model with field merging.

Question 10

Which THREE practices should be followed to secure an Azure AI solution that uses Azure OpenAI Service and Azure AI Search?

Accepted Answer

Use managed identities to authenticate between Azure OpenAI and Azure AI Search.. Option B is correct because managed identities allow Azure OpenAI and Azure AI Search to authenticate securely without storing or rotating credentials. By assigning a managed identity to the Azure OpenAI service, you can grant it access to Azure AI Search via Azure RBAC, eliminating the need for API keys or shared access keys in code or configuration.

Answer

Store API keys in Azure Key Vault but use them directly in application code.

Answer

Place all AI services in a DMZ subnet with public IP addresses.

Question 11

Which TWO Azure services can be used to monitor and analyze the usage costs of an Azure AI solution that includes multiple Cognitive Services accounts?

Accepted Answer

Azure Cost Management + Billing. Azure Cost Management + Billing (C) provides native tools to track, analyze, and optimize cloud spending across all Azure services, including multiple Cognitive Services accounts. It allows you to break down costs by resource, resource group, or tag, and set budgets with alerts. Azure Monitor metrics and logs (E) can capture custom metrics and diagnostic logs from Cognitive Services, enabling you to correlate usage patterns with cost data for deeper analysis.

Answer

Azure Service Health

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Azure Policy

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Azure Advisor

Question 12

You need to provide a team of data scientists with access to an Azure Machine Learning workspace. The data scientists should be able to create and run experiments, but they should not be able to delete the workspace or modify its configuration. Which built-in role should you assign?

Accepted Answer

Contributor. Option A is correct because the Contributor role allows creating and managing resources within the workspace but not deleting the workspace itself. Option B is wrong because Reader is read-only. Option C is wrong because Owner allows full control including deletion. Option D is wrong because User Access Administrator focuses on permissions.

Answer

Reader

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User Access Administrator

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Owner

Question 13

You are deploying an Azure AI multi-agent solution on Microsoft Foundry. The solution uses three agents that must share context and pass tasks among themselves. To ensure reliable orchestration and traceability, which agent pattern should you implement?

Accepted Answer

Sequential agent pattern. The sequential agent pattern is correct because the scenario requires agents to share context and pass tasks among themselves in a reliable, traceable manner. In Microsoft Foundry, the sequential pattern ensures each agent executes in a defined order, passing state and results to the next agent, which provides clear orchestration and full traceability of the workflow.

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Parallel agent pattern

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Sub-agent pattern

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Custom agent pattern

Question 14

Your team uses Azure AI Studio to deploy a large language model endpoint. You need to monitor for prompt injection attacks. Which Azure AI safety feature should you enable?

Accepted Answer

Azure AI Content Safety. Azure AI Content Safety is the correct feature because it provides built-in detection for prompt injection attacks by analyzing user inputs for malicious content, such as jailbreak attempts or indirect injection patterns. This service integrates directly with Azure AI Studio endpoints to filter harmful prompts before they reach the LLM, ensuring compliance with responsible AI practices.

Answer

Azure AI Agent Service

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Azure AI Search

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Azure OpenAI Service

Question 15

You need to restrict access to an Azure AI Language resource so that only a specific virtual network can call the endpoint. Which configuration should you use?

Accepted Answer

Enable a service endpoint or private endpoint for the resource. Option B is correct because Azure AI Language resources can be isolated to a specific virtual network by enabling either a service endpoint (via the Microsoft.CognitiveServices service tag) or a private endpoint (using Azure Private Link). This configuration ensures that only traffic originating from the designated VNet can reach the resource's endpoint, effectively blocking all public internet access. Service endpoints provide a direct, optimized route from the VNet to the resource, while private endpoints assign a private IP from the VNet to the resource, making it accessible only within the VNet.

Answer

Rotate the shared access keys

Answer

Assign a managed identity to the resource

Answer

Configure an IP firewall rule with the VNet's public IP range