AI-200 Practice Test 2 — 30 Questions

Question 1

You are configuring an Azure Kubernetes Service (AKS) cluster to host GPU-accelerated AI model inference workloads using NVIDIA GPUs. Which component must you install in the cluster to enable containerized workloads to utilize the GPU nodes?

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

Accepted Answer

NVIDIA GPU Operator. The NVIDIA GPU Operator automates the management of all NVIDIA software components needed to provision GPUs in Kubernetes.

Answer

NVIDIA Device Plugin for Kubernetes

Answer

KEDA scaler

Answer

Azure Monitor agent

Question 2

Which TWO Azure services can store and serve private Docker container images for AI workloads?

Accepted Answer

Azure Container Instances (pulling from ACR). Azure Container Registry and Azure Container Instances (via image pull secrets) interact with container images, while ACR is the dedicated private registry.

Answer

Azure Cognitive Services

Answer

Azure Bastion

Answer

Azure Logic Apps

Question 3

You are configuring authentication between an Azure Container App running an AI model and an Azure OpenAI resource. To adhere to security best practices, you must avoid storing API keys in environment variables or code. How should you configure this?

Accepted Answer

Configure a system-assigned managed identity on the Container App and grant it Cognitive Services OpenAI User role on the Azure OpenAI resource. Managed identities allow Azure resources to authenticate to services supporting Microsoft Entra authentication without embedding credentials.

Answer

Hardcode the secondary endpoint key into the Docker image build arguments

Answer

Enable anonymous public access on the Azure OpenAI resource for internal virtual network traffic

Answer

Store the Azure OpenAI primary key in an Azure Key Vault and reference it via Container App secrets with plain text retrieval

Question 4

Your data science team pushes container images to Azure Container Registry (ACR). You need to ensure that every image pushed is automatically scanned for known vulnerabilities before being deployed to production. Which ACR feature should you enable?

Accepted Answer

Microsoft Defender for Cloud vulnerability scanning. Microsoft Defender for Cloud integrates with ACR to provide vulnerability scanning for container images upon push or import.

Answer

ACR Tasks

Answer

Azure Policy geo-replication rules

Answer

Content Trust signing

Question 5

You are configuring an Azure Kubernetes Service (AKS) cluster for enterprise AI workloads. Which THREE practices should you implement to enhance cluster security and isolation? (Choose three.)

Accepted Answer

Configure Microsoft Entra Workload Identity for pod-to-Azure service authentication. Enterprise AKS security best practices include enabling Azure Policy for Kubernetes, using Azure RBAC for Kubernetes authorization, and utilizing Workload Identity for secure credential-less access to Azure services.

Answer

Disable TLS on the API server to improve inter-node communication speed

Answer

Share a single service principal across all namespaces for simplified administration

Question 6

You have a large AI model file (5GB) that needs to be loaded into your container at startup. What is the recommended way to handle this?

Accepted Answer

Mount the model from an Azure File Share.. Mounting the file from Azure Blob Storage or an Azure File Share avoids bloating the container image and speeds up deployment.

Answer

Download the model via `curl` at runtime.

Answer

Embed the model in the container image.

Answer

Use a base64 encoded string in the environment variable.

Question 7

Your containerized AI application requires a specific version of a kernel driver that is not installed on the AKS nodes. What is the most efficient way to manage this?

Accepted Answer

Use a privileged InitContainer to load the driver.. Using an InitContainer with appropriate privileges to install the driver on the host is a common pattern for specific hardware needs.

Answer

Mount the /proc filesystem as read-write.

Answer

Run the application as root.

Answer

Rebuild the AKS cluster.

Question 8

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

Accepted Answer

It is a serverless container platform.. ACA is serverless and supports KEDA for scaling.

Answer

You must manage the underlying Kubernetes nodes.

Answer

It is not compatible with Dapr.

Answer

It does not support VNETs.

Question 9

An AKS cluster is configured with KEDA for autoscaling an AI inferencing service based on Azure Queue Storage length. The pods fail to scale. Which component should you inspect first?

Accepted Answer

The ScaledObject resource status.. The ScaledObject is the KEDA custom resource that defines the trigger. If it is misconfigured, the autoscaler will not function.

Answer

The Azure Container Registry webhook settings.

Answer

The Horizontal Pod Autoscaler (HPA) resource directly.

Answer

The Cluster Autoscaler logs.

Question 10

You want to track the latency of your model inference API in production. Which Azure tool should you integrate into your containerized application?

Accepted Answer

Azure Application Insights.. Application Insights is the standard for monitoring performance metrics and telemetry in Azure.

Answer

Azure Storage Queue.

Answer

Azure Event Hubs.

Answer

Azure Data Factory.

Question 11

Which THREE of the following items should be configured to ensure your AI workload in AKS is observable?

Accepted Answer

Prometheus and Grafana.. Logging, metrics, and tracing are the three pillars of observability in AKS.

Answer

Azure Backup.

Answer

Azure Bastion.

Question 12

Your enterprise requires that all container images deployed to Azure Kubernetes Service (AKS) must originate from approved corporate Azure Container Registries (ACRs). How can you enforce this restriction cluster-wide?

Accepted Answer

Configure Azure Policy for Kubernetes with the built-in initiative to restrict container registries. Azure Policy for Kubernetes uses Gatekeeper v3 to audit or enforce cluster behaviors, such as restricting image registries.

Answer

Configure standard Kubernetes Network Policies in the kube-system namespace

Answer

Set up ACR webhook notifications to trigger Azure Functions that delete unauthorized pods

Answer

Modify the kubelet configuration file on every cluster node manually

Question 13

When managing Azure Container Registry (ACR), administrators can use ACR Tasks to automate tasks. Which TWO scenarios are valid use cases for ACR Tasks? (Choose two.)

Accepted Answer

Triggering container image rebuilds automatically when a base image is updated. ACR Tasks supports automated container image builds on source code commits (CI) and automated OS/framework patching base image updates.

Answer

Providing a managed Kubernetes API control plane

Answer

Executing automated container vulnerability scans directly inside registry storage

Answer

Running a persistent, multi-node enterprise database cluster inside ACR

Question 14

Your development team is planning to deploy a containerized natural language processing model to Azure Container Apps. Which TWO features are natively supported by Azure Container Apps for managing application lifecycle and traffic? (Choose two.)

Accepted Answer

Built-in KEDA-based autoscaling including scaling to zero. Azure Container Apps natively supports multi-revision management and traffic splitting between revisions, as well as KEDA autoscaling.

Answer

Automatic deployment of bare-metal hypervisors

Answer

Direct root SSH access to individual container instances for interactive debugging

Answer

Direct manual configuration of control plane Kubernetes master nodes

Question 15

You are containerizing a large language model (LLM) inference API to run in Azure Container Apps. The model weights exceed 15 GB and cause container startup timeouts because the image takes too long to pull from Azure Container Registry (ACR). You need to optimize the container startup performance without reducing the model size. What is the best approach?

Accepted Answer

Enable ACR artifact streaming for the container registry.. ACR artifact streaming allows containers to start immediately by streaming layers on-demand without waiting for the entire image to download locally, significantly reducing cold-start times for large AI container images.

Answer

Upgrade the Azure Container Apps environment to use HTTP/2 protocol.

Answer

Store the model weights in an Azure Blob Storage account and mount them via an ephemeral volume.

Answer

Configure ACR content trust and geo-replication.

Question 16

You have a large image that takes a long time to pull. You want to speed up deployment in AKS. Which feature should you enable?

Accepted Answer

Enable Artifact Streaming in ACR.. Image Pull Secrets are standard, but ACR 'Artifact Streaming' is the specific feature for reducing pull times.

Answer

Use a public mirror for the image.

Answer

Increase the AKS node count.

Answer

Use smaller base images.

Question 17

Which TWO of the following are valid ways to reduce the size of a container image?

Accepted Answer

Use multi-stage Docker builds.. Multi-stage builds and using lighter base images are the two most effective strategies for image size reduction.

Answer

Use the 'latest' tag for all dependencies.

Answer

Enable ACR Geo-replication.

Answer

Install all dependencies in one RUN command.

Question 18

When designing an AI architecture that uses Azure AI Search, which TWO methods can be used to ingest documents and their vector embeddings into the search index? (Choose two)

Accepted Answer

Push API using HTTP POST requests to upload documents directly. Azure AI Search supports pushing data via the Push API (REST/SDK) or pulling data using indexers connected to data sources like Blob Storage or Cosmos DB.

Answer

Direct mounting of an NFS network share as the search index

Answer

FTP file transfer into the search engine storage directory

Answer

Direct SQL Server backup restore (.bak file import)

Question 19

You are designing a data layer architecture for an enterprise AI assistant that requires high-performance vector search, structured filtering, and multi-tenant isolation. Which THREE design patterns should you consider? (Choose three)

Accepted Answer

Combining vector similarity with metadata filters to narrow search scope. Effective AI data layer design patterns include logical partitioning for multi-tenancy, pre-filtering metadata, and hybrid retrieval combining keyword and vector search.

Answer

Storing all tenant data in a single unindexed JSON blob without partition keys

Answer

Hardcoding all user prompts directly into the search index schema

Question 20

When configuring vector search in Azure Cosmos DB for NoSQL, which TWO steps are required to prepare a container for vector search before inserting documents? (Choose two)

Accepted Answer

Define the vectorEmbeddingPolicy at container creation or update. Preparing a Cosmos DB container for vector search requires adding a vector embedding policy and defining vector indexes in the indexing policy.

Answer

Mount an NFS network share for vector file storage

Answer

Install the pgvector extension on the container

Answer

Create a relational foreign key constraint to Azure SQL