AI-200 Practice Test 2 — 10 Questions

Question 1

You have an AI model container hosted in Azure Container Registry. You want to ensure that every container image pushed to the registry is automatically scanned for known vulnerabilities before deployment. Which ACR feature should you enable?

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

Accepted Answer

Microsoft Defender for Cloud vulnerability scanning. Microsoft Defender for Cloud vulnerability scanning is correct because it provides integrated image vulnerability assessment for Azure Container Registry, automatically scanning images on push and continuously re-scanning for newly disclosed CVEs. Enabling the Defender for Containers plan surfaces scan results in Defender for Cloud and can gate deployments via Azure Policy. This directly satisfies the requirement to scan every pushed image before deployment.

Answer

ACR Tasks auto-purge

Answer

Content Trust

Answer

ACR geo-replication

Question 2

You are deploying a web application container to Azure Container Apps and want to enable external HTTPS traffic. Which ingress setting must you configure?

Accepted Answer

Enable ingress with external traffic permitted. To expose a Container App to the public internet over HTTPS, you must enable ingress and set it to accept external traffic. Container Apps then provisions a fully qualified domain name (FQDN) and a managed TLS certificate automatically, terminating HTTPS at the ingress layer. Without external ingress enabled, the app is only reachable inside the environment.

Answer

Set target port to 80 and protocol to TCP

Answer

Disable ingress entirely

Answer

Configure internal ingress only

Question 3

Your AI processing pipeline requires high-throughput streaming ingestion and retention of telemetry data. Which THREE features or capabilities are native to Azure Event Hubs? Each correct answer represents a complete capability.

Accepted Answer

Event Hubs Capture for automatically batching and saving stream data to Azure Storage. Option A is correct because Event Hubs Capture is a native feature that automatically batches streaming data and writes it to Azure Blob Storage or Azure Data Lake Storage (in Avro format) based on a time or size window, satisfying the retention requirement without custom code. Option C is correct because Consumer Groups are a native Event Hubs construct that lets multiple independent applications each maintain their own offset and read the same event stream independently, which is essential for multiple downstream consumers. Option D is correct because Event Hubs partitions the stream and allows multiple receivers to process partitions in parallel, which is the foundation of its high-throughput streaming ingestion and parallel processing model. Option B is not correct because Event Hubs does not natively push events via webhooks for serverless triggers; that pattern belongs to Event Grid, whereas Event Hubs uses AMQP/Kafka pull-based consumption. Option E is not correct because automatic dead-lettering based on a MaxDeliveryCount threshold is a Service Bus queue/subscription feature, not a native Event Hubs capability.

Answer

Native webhook push delivery for discrete serverless event triggers

Answer

Automatic dead-lettering of messages exceeding a MaxDeliveryCount threshold

Question 4

Your AI ingestion pipeline ingests millions of clickstream events per second from IoT devices and streams them into an Azure ML training pipeline. Which Azure service is specifically designed for high-throughput, low-latency telemetry ingestion at this scale?

Accepted Answer

Azure Event Hubs. Azure Event Hubs is designed for high-throughput, low-latency ingestion of telemetry data, capable of handling millions of events per second. It is optimized for streaming scenarios like IoT telemetry and clickstream data, making it ideal for this use case.

Answer

Azure Notification Hubs

Answer

Azure Event Grid

Answer

Azure Service Bus Queues

Question 5

You are designing an application that requires low-latency vector search for a high-traffic AI chatbot. You need to ensure the vector index remains performant as the dataset grows into millions of documents. Which index configuration in Azure AI Search should you implement to optimize for speed over absolute recall accuracy?

Accepted Answer

HNSW. HNSW (Hierarchical Navigable Small World) is a graph-based approximate nearest neighbor (ANN) algorithm that builds a multi-layer navigable graph, delivering sub-linear query latency with high recall. In Azure AI Search, HNSW is the recommended index configuration for high-traffic, low-latency vector search over millions of documents when you can trade a small amount of recall for speed.

Answer

Flat Indexing

Answer

Exhaustive KNN

Answer

Partitioned Indexing

Question 6

You are designing the data architecture for an AI-powered document search application. You choose Azure AI Search because you need multi-lingual support, faceted navigation, and vector search. What is the maximum number of vector fields allowed per index in Azure AI Search?

Accepted Answer

Multiple vector fields are supported per index. Azure AI Search supports multiple vector fields per index, allowing you to store and query different embeddings (e.g., text, image, or multi-model vectors) within the same index. Each vector field is defined with its own dimensions and similarity metric, and you can target specific fields in vector queries. This flexibility is essential for hybrid and multi-modal search scenarios.

Answer

Exactly one vector field per index

Answer

A maximum of two vector fields

Answer

Vector fields are not supported in Azure AI Search

Question 7

You need to ensure that all data sent to Azure OpenAI Service is encrypted at rest using a custom encryption key that your organization controls and rotates. Which feature must you configure?

Accepted Answer

Customer-managed keys (CMK) stored in Azure Key Vault. Customer-managed keys (CMK) in Azure Key Vault let you supply your own encryption key that Azure OpenAI uses for data-at-rest encryption, and you control rotation and revocation through Key Vault. This satisfies the requirement for organization-controlled, rotatable encryption keys for stored data.

Answer

Client-side encryption using PGP keys before sending HTTP payloads

Answer

Azure Information Protection sensitivity labels applied via Microsoft Purview

Answer

Transparent Data Encryption (TDE) configured via SQL Server Management Studio

Question 8

Your team is choosing between using Azure AI Search or Cosmos DB for NoSQL for a new project. Which TWO factors are key considerations that favor Azure AI Search?

Accepted Answer

Need for deep integration with full-text search (BM25) and hybrid search.. Option A is correct because Azure AI Search is purpose-built as a search engine that natively supports full-text search using the BM25 ranking algorithm as well as hybrid search that combines keyword and vector queries, which Cosmos DB for NoSQL does not provide out of the box. Option D is correct because Azure AI Search includes built-in semantic re-ranking (semantic ranker/L2 reranking) that reorders results using deep-learning models to improve relevance and accuracy, a capability Cosmos DB for NoSQL lacks natively. Option B is not a factor favoring Azure AI Search, since petabyte-scale storage is a strength of Cosmos DB for NoSQL rather than a search service. Option C is not a factor favoring Azure AI Search, because high-frequency transactional ACID updates to metadata are handled by Cosmos DB for NoSQL's transactional capabilities, not by a search index. Option E is not a factor favoring Azure AI Search, as lowest possible database-level latency is a characteristic of Cosmos DB for NoSQL's globally distributed, low-latency data plane rather than the search service.

Answer

Requirement to store petabytes of data.

Answer

Requirement for high-frequency transactional ACID updates to metadata.

Answer

Need for lowest possible latency at the database level.

Question 9

An application publishes custom events to an Azure Event Grid topic. You want to inspect the dead-lettered events that failed delivery after the maximum retry period. Where must you configure the dead-letter destination?

Accepted Answer

Azure Blob Storage container. Event Grid dead-lettering requires an Azure Blob Storage container as the destination, configured on the event subscription. When an event fails all delivery retries (default 30 attempts over 24 hours), it is written to that container as a blob so you can inspect and reprocess it. Blob Storage is the only supported dead-letter target for Event Grid.

Answer

Azure SQL Database table

Answer

Local App Service temporary file system

Answer

Azure Service Bus Dead-Letter Queue

Question 10

You need to restrict access to an Azure OpenAI resource so that only requests originating from a specific Azure Virtual Network are permitted. What should you configure?

Accepted Answer

Configure the Azure OpenAI resource networking settings to allow access from 'Selected networks' and add your Virtual Network subnet.. Virtual network rules (service endpoints or private endpoints) on the Azure OpenAI firewall can restrict access to specific VNets.

Answer

Enable Cross-Origin Resource Sharing (CORS) and specify the VNet IP range.

Answer

Assign the Cognitive Services Contributor role to the Virtual Network principal.

Answer

Enable Microsoft Defender for Cloud on the Virtual Network.