AI-200 Practice Test 11 — 15 Questions

Question 1

You are configuring vector indexing in Azure Cosmos DB for MongoDB (vCore). You need to choose an indexing type for your vector property to balance query performance and recall accuracy for high-dimensional data. Which vector index type should you select for approximate nearest neighbor (ANN) search?

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

Accepted Answer

HNSW (Hierarchical Navigable Small World). HNSW (Hierarchical Navigable Small World) is a graph-based approximate nearest neighbor algorithm that builds a multi-layer navigable graph, delivering high recall with low latency for high-dimensional vectors. In Azure Cosmos DB for MongoDB vCore, HNSW is the supported vector index type for ANN search, and it is the recommended choice when you need to balance query performance and recall accuracy. FULLTEXT, B-Tree, and HASH indexes are not designed for vector similarity search and cannot perform ANN queries.

Answer

FULLTEXT index

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B-Tree index

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HASH index

Question 2

You need to check the health status of Azure AI services globally and see if any regional outages are currently impacting your deployed models. Which Azure tool should you consult?

Accepted Answer

Azure Service Health. Azure Service Health provides personalized and global views of Azure service issues, planned maintenance, health advisories, and security advisories that may affect your deployed resources. It is the correct tool to check for regional outages impacting Azure AI services and your models.

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Azure Cost Management

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Azure Policy

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Azure Advisor

Question 3

You are designing a multi-tenant AI ingestion pipeline using Azure Event Hubs. You need to ensure that low-priority tenants cannot starve high-priority tenants of partition resources. Which feature should you implement?

Accepted Answer

Deploy separate Event Hubs namespaces for high-priority and low-priority tenants.. Event Hubs throughput and partition resources are scoped to a namespace, so tenants sharing a single namespace compete for the same throughput units and partitions. Deploying separate namespaces for high-priority and low-priority tenants physically isolates their throughput units, partitions, and throttling limits, preventing noisy-neighbor starvation. This is the standard multi-tenant isolation pattern for Event Hubs.

Answer

Set the Capture interval to 60 seconds for low-priority partitions.

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Configure RBAC permissions to restrict low-priority tenants to Reader roles.

Answer

Enable Azure DDoS Protection Standard on the Event Hubs consumer group.

Question 4

You are troubleshooting a performance issue where an Azure AI Search indexer fails to complete within the scheduled execution window when processing large PDF documents. What is the most effective configuration change to resolve the timeout issue?

Accepted Answer

Configure the indexer maxRunTime property and scale out search units or adjust batch size. Indexer timeouts on large PDFs are typically caused by the indexer exceeding the scheduled run window while skillset enrichment and document cracking proceed slowly. Increasing maxRunTime extends the allowed execution window, and scaling out search units (or reducing batch size) increases throughput so the indexer completes within the schedule. These are the documented levers for resolving indexer timeout issues in Azure AI Search.

Answer

Convert all vector fields to Edm.String

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Switch the search service to the Free tier

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Delete all semantic configurations from the index

Question 5

You are configuring geo-disaster recovery for an Azure Service Bus Premium namespace containing critical financial transactions. A regional outage occurs. After initiating a failover to the secondary region, what happens to the alias pointing to the namespace?

Accepted Answer

The alias automatically points to the secondary namespace, and pairing is broken.. After a geo-disaster recovery failover in Azure Service Bus Premium, the alias automatically points to the secondary namespace and the pairing between primary and secondary is broken. The alias is a stable connection string endpoint that clients use, so applications do not need to change connection strings; however, the former primary becomes unusable until it is re-paired. This is the documented behavior of Service Bus Geo-DR failover.

Answer

The secondary namespace remains in Read-Only mode until manually unlocked.

Answer

The alias becomes invalid, and you must deploy a new Service Bus namespace from scratch.

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Unreplicated messages in the primary queue are automatically migrated in real-time.

Question 6

You are designing a vector search solution using Azure AI Search. Which THREE of the following are necessary steps to configure an index to support vector search?

Accepted Answer

Define a 'vectorSearch' configuration within the index schema.. Option A is correct because the index schema must include a 'vectorSearch' configuration block that declares the vector search algorithms (e.g., HNSW or exhaustive KNN) and the profiles used by the index. Option C is correct because each vector field must reference a 'vectorSearchProfile' that ties the field to a specific algorithm and vectorizer configuration defined in the 'vectorSearch' section. Option E is correct because Azure AI Search represents vector embeddings as 'Collection(Edm.Single)', a collection of single-precision floats, which is the required data type for vector fields. Option B is incorrect because setting the index to 'ReadOnly' mode is unrelated to vector search configuration and would only prevent updates to the index. Option D is incorrect because 'Edm.String' is used for text fields, not vector fields, and would not store the numeric embedding arrays required for vector search.

Answer

Set the index to 'ReadOnly' mode.

Answer

Ensure all vector fields are set to 'Edm.String'.

Question 7

Your team is building an asynchronous order processing pipeline. If a downstream AI service fails to process a message from a Service Bus queue after 5 delivery attempts, the message must be automatically removed from active processing and preserved for manual inspection. What should you configure?

Accepted Answer

Configure the Max Delivery Count property on the queue and enable dead-lettering on message expiration or failure.. Configuring Max Delivery Count on the queue (for example, 5) combined with dead-lettering on message expiration or delivery failure ensures that after five unsuccessful delivery attempts the message is moved to the dead-letter queue (DLQ) rather than being retried indefinitely or discarded. The DLQ preserves the message payload and failure metadata for manual inspection and reprocessing. This is the native Service Bus mechanism for poison-message handling.

Answer

Enable Duplicate Detection with a history window of 5 attempts.

Answer

Set the AutoDeleteOnIdle property on the queue to 5 minutes.

Answer

Implement Event Grid dead-lettering pointing to an Azure Blob Storage container.

Question 8

Your Azure AI application relies on Azure OpenAI and Azure AI Search. You need to troubleshoot a sudden surge in HTTP errors and latency. Which THREE of the following Azure Monitor / Application Insights features or tools should you use to diagnose the issue? (Choose three)

Accepted Answer

Application Map in Application Insights to identify downstream dependency latency bottlenecks.. Application Map visualizes dependencies and latency bottlenecks, Metrics explorer tracks token consumption and throttling counters, and Log Analytics enables KQL queries for specific exception traces.

Answer

Azure Cost Management recommendation advisor for server resizing.

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Azure Bastion diagnostic logs for RDP login failures.

Question 9

You are building an AI search solution using Azure AI Search. You want to ensure that users searching for acronyms or synonyms receive relevant results even if the exact keyword does not appear in the document. Which feature should you configure?

Accepted Answer

Synonym maps. Synonym maps in Azure AI Search let you define equivalence rules so that a query term expands to its synonyms or acronym expansions at query time. This ensures documents containing the full term are returned even when the user searches with an acronym, and vice versa. Synonym maps are applied per-field and are the correct feature for handling acronyms and synonyms.

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Scoring profiles

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Semantic ranker

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Vector profiles

Question 10

You are designing a secure enterprise AI architecture on Azure. Which TWO of the following practices should you implement to secure credentials and service access? (Choose two)

Accepted Answer

Use system-assigned or user-assigned managed identities for Azure service-to-service authentication.. Option A is correct because managed identities (system-assigned or user-assigned) let Azure services authenticate to resources such as Key Vault, Storage, and Azure OpenAI without embedding any credentials in code or configuration, eliminating secret sprawl and enabling Microsoft Entra ID token-based access. Option C is correct because Azure Key Vault is the dedicated service for storing and controlling access to runtime secrets, API keys, connection strings, and certificates, with RBAC, access policies, soft-delete, purge protection, and auditing. Option B is wrong because committing API keys and connection strings as plain text in Git exposes them to anyone with repository access and to history scraping, violating secret-management best practices. Option D is wrong because granting subscription Owner to mobile client applications violates least privilege and would let a compromised app modify or delete any resource in the subscription. Option E is wrong because disabling TLS on internal microservice traffic removes encryption in transit, enabling eavesdropping and man-in-the-middle attacks for a negligible throughput gain.

Answer

Store API keys and connection strings as plain text in Git repository configuration files.

Answer

Grant subscription Owner permissions to all mobile client applications.

Answer

Disable TLS encryption on internal microservice communication to improve network throughput.

Question 11

Your enterprise AI solution runs on Azure Kubernetes Service (AKS) and utilizes Azure Key Vault to store secrets and API keys for cognitive services. You need to provide pods with secure, credential-less access to Azure Key Vault without storing connection strings in Kubernetes secrets or environment variables. Which integration should you implement?

Accepted Answer

Azure Key Vault Provider for Secrets Store CSI Driver with Azure AD Workload Identity. The Azure Key Vault Provider for Secrets Store CSI Driver mounts Key Vault secrets directly into pods as volumes, and when combined with Microsoft Entra ID Workload Identity, the pod authenticates to Key Vault using a federated Kubernetes service account token — no stored credentials, connection strings, or environment variables. This is the recommended credential-less pattern for AKS.

Answer

Kubernetes Service Account tokens mapped to Key Vault access policies via static connection strings

Answer

A Kubernetes CronJob that pulls keys from Key Vault and creates sealed secrets

Answer

Azure Container Instances virtual nodes with managed system-assigned identities

Question 12

You are deploying an AI model container to Azure Container Apps. The container requires persistent storage to cache downloaded Hugging Face model weights across container restarts. Which storage type should you attach to the Container App?

Accepted Answer

Azure Files mount via Container Apps storage configuration. Azure Container Apps supports mounting Azure Files shares as persistent volumes through the storage configuration at the environment or app level. Azure Files is the only fully managed, SMB/NFS-based shared file system that Container Apps can mount natively, and it persists independently of the container replica lifecycle, making it ideal for caching model weights across restarts.

Answer

Azure Managed Disks (Premium SSD) direct attach

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Azure Blob Storage FUSE driver

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Ephemeral emptyDir volume

Question 13

Your application emits custom events to an Azure Event Grid topic. You want to test your webhook endpoint locally during development without deploying your code to Azure. Which tool should you use to receive events directly from Event Grid?

Accepted Answer

Deploy the Event Grid Viewer sample web app to an accessible public URL or use ngrok to tunnel your local port.. Event Grid delivers events via HTTP POST to a webhook endpoint, so the endpoint must be reachable from the public internet. During local development, you either deploy the Event Grid Viewer sample to a publicly accessible URL or use ngrok to create a public tunnel that forwards to your localhost port. This lets Event Grid push events directly to your local debugging session without deploying your application to Azure.

Answer

Use Azure Bastion to connect your localhost to the Event Grid topic.

Answer

Configure a local SQL Server Express trigger.

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Attach an Azure Service Bus queue directly as a local debugging breakpoint.

Question 14

Your application publishes custom events to an Azure Event Grid topic. You want to ensure that event publishers transmit data over secure HTTPS endpoints only. How should you enforce this?

Accepted Answer

Event Grid enforces HTTPS by default for all custom topic publishing endpoints.. Azure Event Grid custom topics expose a publishing endpoint that only accepts HTTPS (TLS 1.2+) requests — there is no HTTP listener. Publishers must POST events to the topic's HTTPS URL using the `aeg-sas-key` header or Microsoft Entra ID token. Because HTTPS is the only supported transport, no additional configuration (certificates, firewalls, or gateways) is required to enforce it.

Answer

You must install a self-signed SSL certificate on the publisher client machine.

Answer

Configure an Azure Firewall rule allowing port 80 outbound.

Answer

You must configure an Azure Application Gateway in front of the Event Grid topic.

Question 15

You are configuring a Vector Index in Azure AI Search. You need to ensure that the vector similarity search is performed using the Cosine distance metric. Where is this configuration specified?

Accepted Answer

In the 'vectorSearch' section of the index definition.. In Azure AI Search, the vector search configuration, including the similarity metric such as cosine, dotProduct, or euclidean, is specified in the 'vectorSearch' section of the index definition. This section defines algorithms (like HNSW) and profiles that bind the metric to vector fields. The metric is set at the algorithm level and referenced by vector fields.

Answer

In the indexer definition.

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In the search query payload.

Answer

In the field definitions within the index.