AI-200 Practice Test 17 — 15 Questions

Question 1

You are writing a query in Azure Cosmos DB for NoSQL to retrieve documents based on vector similarity against a target embedding. Which built-in SQL function should you use in the ORDER BY clause?

Accepted Answer

VectorDistance(). Azure Cosmos DB for NoSQL exposes the VectorDistance() built-in function, which computes the similarity/distance between a stored vector property and a query vector, and is used inside ORDER BY to rank results by similarity. It supports cosine, dot product, and Euclidean metrics via an optional third argument. This is the documented function for vector search queries in the NoSQL API.

Answer

CosSimilarity()

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EmbeddingDistance()

Answer

GetVectorDistance()

Question 2

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 3

Which distance metric in Azure Cosmos DB vector search calculates the shortest straight-line segment between two points in a multi-dimensional space?

Accepted Answer

euclidean. Euclidean distance (D) measures the straight-line (L2) distance between two vectors in multi-dimensional space, computed as the square root of the sum of squared differences across dimensions. It is the metric that literally corresponds to the geometric 'shortest straight-line segment' between two points, making it the correct answer for Cosmos DB vector search.

Answer

dotproduct

Answer

hamming

Answer

cosine

Question 4

You are building an event-driven AI workflow where an Azure Event Grid event triggers an Azure Function. To ensure that the function handles the Event Grid handshake validation handshake correctly when the subscription is created, what must your function code include?

Accepted Answer

Code to handle the SubscriptionValidationEvent and return the validation code.. When Event Grid creates a webhook subscription, it sends a SubscriptionValidationEvent to the endpoint. The function must detect this event type, extract the validationCode from the event data, and return it in the HTTP response so Event Grid can confirm endpoint ownership. Without this handshake handling, the subscription creation fails and events are never delivered.

Answer

An Event Hubs consumer group checkpoint store configuration.

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A Service Bus session lock renewal loop.

Answer

An AMQP listener connection string.

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

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Cognitive Services Contributor

Answer

Storage Blob Data Reader

Question 6

Which tool in Azure Portal allows you to test search queries, inspect index schemas, and view JSON responses for Azure AI Search?

Accepted Answer

Search explorer. Search explorer is the built-in query console in the Azure portal for Azure AI Search. It lets you submit simple, full, or Lucene queries against a selected index, inspect the index schema (fields, attributes, analyzers), and view the raw JSON response documents returned by the service. This makes it the correct tool for testing search queries and validating index behavior directly from the portal.

Answer

Metrics Advisor

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Data Explorer

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Log Analytics

Question 7

You are designing an event-driven AI document processing pipeline. Incoming PDF documents are uploaded to Azure Blob Storage, triggering an Event Grid event. The event triggers an Azure Function that downloads the PDF, processes it with Azure AI Document Intelligence, and saves results to Azure Cosmos DB. Under high load, duplicate events are occasionally received by the function, causing duplicate Cosmos DB records. How should you design the Azure Function to handle idempotency?

Accepted Answer

Implement idempotency in the Azure Function by checking if the document record already exists in Cosmos DB or using an upsert operation with a deterministic ID.. Idempotency in an at-least-once event pipeline is achieved by making the consumer's write operation idempotent — either by checking for an existing record before insert or by using an upsert with a deterministic ID derived from the event. This ensures duplicate Event Grid deliveries produce the same final state in Cosmos DB without creating duplicate records.

Answer

Set the Event Grid retry count to zero.

Answer

Deploy an Azure Service Bus queue in front of Blob Storage to serialize all requests into a single partition.

Answer

Configure Event Grid delivery mode to 'Exactly-Once' in the subscription settings.

Question 8

You are configuring an Azure Service Bus Topic and Subscriptions for an AI text classification system. Which THREE filter types are supported on Service Bus subscriptions for routing messages? Each correct answer represents a valid filter type.

Accepted Answer

Boolean Filters (True/False filters). Service Bus subscriptions support exactly three filter types: Boolean filters, SQL filters, and Correlation filters. Option A (Boolean Filters) is correct because a TrueFilter (1=1) captures all messages to a subscription and a FalseFilter (1=0) blocks all messages, which is useful for a catch-all or disabled subscription in the classification pipeline. Option D (SQL Filters) is correct because they use SQL-like expressions evaluated against message system and user properties (for example, sys.Label='sports' AND priority>5), enabling content-based routing of text classification messages. Option E (Correlation Filters) is correct because they match on properties such as CorrelationId, MessageId, Label, ReplyTo, and custom properties, providing efficient exact-match routing for AI workloads. Option B (Regex Pattern Matching Filters) is not a supported Service Bus filter type, and Option C (Machine Learning Inference Filters) does not exist as a native subscription filter; both are invalid for this scenario.

Answer

Regex Pattern Matching Filters

Answer

Machine Learning Inference Filters

Question 9

You are configuring an Azure AI Search index where text fields are automatically analyzed using language-specific rules. Which property on an Edm.String field specifies the language analyzer (e.g., 'en.microsoft')?

Accepted Answer

analyzer. In Azure AI Search, the 'analyzer' property on an Edm.String field specifies the language analyzer (e.g., 'en.microsoft', 'fr.lucene') that governs tokenization, stemming, and stop-word removal for that field. Setting it per-field enables language-specific text processing so queries match documents correctly across languages.

Answer

tokenizerType

Answer

languageMapping

Answer

vectorProfile

Question 10

You are managing an Azure Kubernetes Service (AKS) cluster that runs high-throughput AI model training jobs using NVIDIA Tensor Core GPUs. Pods frequently fail to schedule because of insufficient GPU memory across existing nodes. You need to ensure the cluster automatically provisions new GPU-enabled worker nodes when resource demands increase. What should you configure?

Accepted Answer

Enable the Kubernetes Cluster Autoscaler on a node pool containing GPU virtual machine sizes.. The Kubernetes Cluster Autoscaler watches for pods that cannot be scheduled due to insufficient resources and automatically scales the node pool up or down. When configured on a node pool that contains GPU-enabled VM sizes (such as NC or ND series), it will provision additional GPU nodes when training pods are pending due to GPU memory constraints. This is the only option that adds new worker nodes rather than scaling existing pods or reacting to events.

Answer

Configure KEDA (Kubernetes Event-driven Autoscaling) with a Prometheus scaler.

Answer

Configure the Horizontal Pod Autoscaler (HPA) with custom GPU metrics.

Answer

Deploy the Azure Container Storage operator with GPU caching enabled.

Question 11

You are configuring vector search on an Azure AI Search index using a custom vectorizer that points to an external embedding endpoint. Which authentication method is recommended and natively supported for securely connecting Azure AI Search to the Azure OpenAI endpoint?

Accepted Answer

Managed Identity (system-assigned or user-assigned). Managed Identity is the recommended and natively supported authentication method for Azure AI Search to securely connect to Azure OpenAI when using a custom vectorizer. It leverages Microsoft Entra ID to provide an identity for the search service, eliminating the need to manage credentials. The identity is automatically managed by Azure and can be granted permissions to the Azure OpenAI resource, ensuring secure access without storing secrets.

Answer

OAuth2 client credentials grant with Azure AD tenant federation

Answer

Shared Access Signature (SAS) tokens

Answer

Basic authentication with API keys stored in index metadata

Question 12

Which TWO of the following are true about Azure Container Apps?

Accepted Answer

It is a serverless container platform.. Azure Container Apps is a fully managed, serverless container platform, so option B is correct: it abstracts away the Kubernetes control plane and nodes, letting you run containers without provisioning or managing infrastructure. Option D is also correct because Azure Container Apps uses KEDA (Kubernetes Event-driven Autoscaling) under the hood to scale containers based on events such as queues, HTTP traffic, or custom metrics. Option A is wrong because node management is handled by the platform, not the user. Option C is wrong because Azure Container Apps has built-in Dapr integration for microservice building blocks. Option E is wrong because Azure Container Apps supports virtual network (VNET) integration for inbound and outbound connectivity.

Answer

You must manage the underlying Kubernetes nodes.

Answer

It is not compatible with Dapr.

Answer

It does not support VNETs.

Question 13

You are designing an enterprise search architecture that combines Azure AI Search and Azure OpenAI. Which THREE strategies help optimize hybrid search relevance and retrieval quality? Choose three.

Accepted Answer

Tune HNSW parameters (m and efSearch) based on recall and latency trade-offs. Option A is correct because HNSW parameters directly control the approximate nearest neighbor graph: increasing m improves recall at the cost of memory and index build time, while efSearch tunes the query-time candidate list to balance recall against latency, making it a core lever for hybrid search relevance. Option B is correct because Reciprocal Rank Fusion (RRF) merges the ranked result lists from keyword (BM25) and vector queries into a single ranking using 1/(k + rank) scoring, which is exactly how Azure AI Search combines lexical and vector results in hybrid mode. Option C is correct because the semantic ranker applies deep-learning re-ranking (Microsoft's cross-encoder models) over the top results, promoting semantically relevant documents that lexical or vector scores alone may rank lower. Option D is not correct because disabling OData filters does not improve vector recall and removes useful precision controls; filters are applied alongside vector search to narrow the candidate set. Option E is not correct because storing embeddings as uncompressed plaintext in Blob Storage is inefficient and unrelated to search relevance; embeddings should be stored in the search index as Collection(Edm.Single) vectors, ideally with compression such as scalar or binary quantization.

Answer

Disable all OData filters to maximize vector recall

Answer

Store all embeddings as uncompressed plaintext strings in Blob Storage

Question 14

You are configuring network security for an enterprise Azure Service Bus Premium namespace. Which THREE networking features can you configure to secure the namespace? (Choose three)

Accepted Answer

Private endpoints using Azure Private Link. Option A (Private endpoints using Azure Private Link) is correct because Service Bus Premium supports Private Link, which assigns a private IP from your VNet to the namespace and removes exposure to the public internet, allowing secure access over the Microsoft backbone network. Option C (IP firewall rules) is correct because Service Bus Premium lets you restrict access to specific public IP addresses or CIDR ranges via the namespace's networking firewall, blocking all other public traffic by default. Option D (Virtual Network (VNet) service endpoints) is correct because Service Bus Premium supports VNet service endpoints, which extend your VNet identity to the service over the Azure backbone and let you restrict access to specific subnets. Option B is incorrect because Event Grid MQTT broker certificate authentication applies to Event Grid's MQTT support, not to Azure Service Bus. Option E is incorrect because Blob storage container access policies are a storage feature unrelated to securing a Service Bus namespace.

Answer

Event Grid MQTT broker certificate authentication

Answer

Blob storage container access policies

Question 15

You want to receive an email notification whenever monthly spending on your Azure OpenAI Service exceeds $5,000. Which Azure feature should you configure?

Accepted Answer

Cost Management budget with an alert threshold set at the desired dollar amount. Azure Cost Management budgets allow you to define spending thresholds and attach action groups or email recipients for notifications.

Answer

Azure Service Health incident alert

Answer

Azure Advisor security recommendation

Answer

Azure Monitor Metric alert on CPU utilization