AI-200 Practice Test 29 — 15 Questions

Question 1

Your Azure Machine Learning workspace is secured inside a virtual network with private endpoints. To ensure that data scientists can securely train models and access data stores without exposing resources to the public internet, which THREE of the following configurations must be established? (Choose three)

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

Accepted Answer

Private endpoints for associated Azure Storage accounts, Key Vault, and Azure Container Registry.. Securing workspaces requires private endpoints for the workspace storage accounts/key vault, disabling public network access, and configuring peered virtual networks or Azure Bastion/VPN for workspace access.

Answer

Public IP addresses assigned directly to every compute instance for direct SSH debugging.

Answer

Enabling anonymous public scoring endpoints for all model deployments.

Question 2

You are configuring network security for an Azure Machine Learning workspace. Compute instances must be accessible via Jupyter Lab, but no public IP addresses can be associated with the compute instances. Which configuration is required?

Accepted Answer

Create the compute instance with no public IP and configure a private endpoint for the workspace, accessing via Azure Bastion or workspace workspace-managed network isolation.. Azure Machine Learning compute instances can be created with 'No Public IP' enabled, and administrators use Azure Bastion or workspace private endpoints to access them securely.

Answer

Use ExpressRoute with public peering to route traffic directly to the compute instance public IP.

Answer

Deploy the compute instance in a public subnet with Network Security Group (NSG) rules blocking port 22.

Answer

Enable Azure Firewall with DNAT rules routing traffic to the compute instance public IP.

Question 3

Your enterprise application uses Azure Event Grid. Which TWO event schemas are natively supported when publishing events to an Event Grid custom topic? (Choose two)

Accepted Answer

CloudEvents 1.0 schema. Azure Event Grid natively supports the Event Grid Schema and the CloudEvents 1.0 Schema.

Answer

Apache Kafka record batch binary schema

Answer

AMQP 1.0 binary stream envelope

Answer

SOAP 1.2 XML messaging schema

Question 4

You are designing an AI streaming architecture using Azure Event Hubs in a Dedicated cluster. You need to monitor capacity utilization to ensure the cluster does not exceed its allocated Processing Units (PUs). Which metric should you track in Azure Monitor?

Accepted Answer

Dedicated Cluster Memory and CPU Usage / Processing Units (PUs) Utilization metrics.. Azure Event Hubs Dedicated clusters are measured in Processing Units (PUs). You monitor CPU usage and PU utilization metrics in Azure Monitor to determine if scaling out the dedicated cluster is necessary.

Answer

Service Bus Active Message Count.

Answer

Event Grid Delivery Success Rate percentage.

Answer

Storage Account Blob Capacity utilization.

Question 5

You are managing costs for multiple Azure AI services used by different business units. You need to track expenditure against specific departmental budgets and receive automated alerts when spending exceeds 80% of the allocated budget. Which Azure feature should you use?

Accepted Answer

Azure Cost Management Budgets with alert conditions. Azure Cost Management budgets allow you to set monetary or usage thresholds and configure automated alert notifications when thresholds are approached or exceeded.

Answer

Azure Advisor cost recommendations

Answer

Azure Monitor autoscale settings

Answer

Azure Service Health alerts

Question 6

You are writing a Python script to query an Azure AI Search index using the azure-search-documents SDK. You want to retrieve both vector matches and keyword matches using hybrid search. Which class should you instantiate to represent the vector query?

Accepted Answer

VectorizedQuery. The VectorizedQuery class in the Azure AI Search Python SDK is used to construct vector queries for hybrid or vector-only search requests.

Answer

EmbeddingQueryClient

Answer

HnswSearchRequest

Answer

CosmosVectorSearch

Question 7

You want to check the current monthly spend on your Azure OpenAI Service resource and identify which model deployments are consuming the most budget. Which Azure portal tool should you use?

Accepted Answer

Cost Analysis in Azure Cost Management + Billing. Cost Analysis in Azure Cost Management allows you to filter and group costs by resource, service, and meter to analyze spending patterns.

Answer

Azure Security Center

Answer

Azure Monitor Metrics explorer

Answer

Azure Resource Health

Question 8

You are optimizing costs for an AI workload running on Azure Kubernetes Service (AKS). You notice that GPU node pools are underutilized during weekends. You want to scale down the GPU node pool to 0 nodes on weekends and scale back up on Monday mornings. What Kubernetes native feature or Azure integration should you use?

Accepted Answer

AKS cluster autoscaler configured with node pool scaling profiles down to zero, or Azure Automation runbooks invoking az aks nodepool scale. Azure Kubernetes Service supports cluster autoscaler and user node pools that can be scaled, or Azure DevOps / GitHub Actions pipelines with Azure CLI commands, but AKS cluster autoscaler natively supports scaling pools down to 0 when configured with node pool stop/start or autoscaler profiles.

Answer

Delete the entire AKS cluster every Friday night and recreate it every Monday using ARM templates

Answer

Use Azure Policy to deny GPU pod scheduling on weekends

Answer

Configure Azure Cost Management to automatically pause billing for GPU SKUs on weekends

Question 9

You are optimizing query performance for an Azure AI Search index experiencing high query volumes with vector search. You need to scale out query processing capabilities without increasing index build time. Which action should you perform?

Accepted Answer

Increase the number of search units by adding replica instances. To scale out query throughput (QPS) and handle higher query load for vector search in Azure AI Search, you should increase the number of replica units.

Answer

Rebuild the index using exhaustiveKnn

Answer

Increase the number of partition instances

Answer

Upgrade the search service from Standard to Basic tier

Question 10

You are designing an AI search architecture that requires handling millions of documents with sub-second vector similarity queries. You choose Azure AI Search. How does Azure AI Search ensure high query throughput for vector indexes?

Accepted Answer

By utilizing HNSW approximate nearest neighbor indexing combined with multi-replica scale-out. Azure AI Search uses HNSW approximate nearest neighbor graphs combined with multi-replica scale-out architecture to deliver high throughput and low latency.

Answer

By caching every possible query result indefinitely in memory

Answer

By executing sequential full table scans across all storage nodes simultaneously

Answer

By converting all vectors into relational database tables with SQL foreign keys

Question 11

Your Azure Event Hubs namespace is experiencing high throughput spikes from AI inference nodes. You notice that some client producers are receiving 'QuotaExceededException' errors. What is the root cause and how should you remediate it?

Accepted Answer

Ingress or egress limits have been exceeded; enable Auto-Inflate on the Event Hubs namespace.. Event Hubs throughput is governed by Throughput Units (TUs) or Processing Units (PUs) in dedicated clusters. Exceeding ingress or egress limits triggers QuotaExceededException. Remediation involves scaling up TUs or enabling Auto-Inflate.

Answer

The partition count has been exceeded; decrease the number of consumer groups.

Answer

The SAS token has expired; regenerate the connection string.

Answer

The message retention period has expired; increase retention days.

Question 12

You have deployed an AI model in Azure Machine Learning. You want to set up an alert that triggers an email to the operations team whenever the CPU utilization of the compute instance exceeds 90% for longer than 15 minutes. Which Azure Monitor feature should you configure?

Accepted Answer

Azure Monitor metric alerts with an action group. Azure Monitor metric alerts allow you to monitor resource metrics like CPU utilization and trigger alert actions such as sending emails when conditions are met.

Answer

Azure Cost Management anomaly alerts

Answer

Azure Policy remediation tasks

Answer

Azure Service Health planned maintenance alerts

Question 13

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.. Azure Service Bus provides a dead-letter queue (DLQ) feature. When max delivery count is exceeded, the message is automatically moved to the DLQ for troubleshooting.

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 14

You are provisioning an Azure AI Search service to support hybrid search, combining full-text lexical search and vector search. Which tier is the minimum required to support vector search capabilities at enterprise scale?

Accepted Answer

Basic tier. Azure AI Search supports vector search starting from the Basic tier, though Standard tiers (S1, S2, etc.) and Storage Optimized tiers are recommended for production enterprise scale.

Answer

Free tier

Answer

Storage Optimized L1

Answer

Standard 3 High Density (S3 HD)

Question 15

You are integrating an Azure Event Hubs namespace with Azure Machine Learning for real-time model training. You need to archive raw telemetry data into Azure Data Lake Storage Gen2 in Apache Parquet format without writing custom code. Which feature should you enable?

Accepted Answer

Event Hubs Capture. Event Hubs Capture automatically packages streaming data into Avro or Parquet files and stores them directly in Azure Blob Storage or Azure Data Lake Storage Gen2.

Answer

Event Grid system topic with a Storage Blob export endpoint

Answer

Azure Stream Analytics job with a Blob output sink

Answer

Service Bus Geo-Disaster Recovery replication