How should I use these Containerized AI Workloads practice questions?

Read each scenario carefully and choose your answer before revealing the explanation. Then check why your choice was right or wrong. Repeat until the reasoning feels automatic.

Can I practise just Containerized AI Workloads questions in a focused session?

Yes — use the session launcher on this page to start a 10-, 20-, 30- or 50-question session drawn entirely from the Containerized AI Workloads domain.

AI-200 · topic practice

Containerized AI Workloads practice questions

This domain covers packaging and running AI models in containers on Azure. You must know how Azure Container Registry handles image scanning and vulnerability detection, how Azure Container Apps configures ingress and HTTPS, and how AKS controls pod resources, scheduling, and availability through Kubernetes manifests and node topology.

Courseiva uses original exam-style practice questions designed for learning and revision. The goal is to understand the concepts, recognise exam patterns, and improve through explanations — not memorise copied exam dumps.

Editorial oversight:Johnson Ajibi· MSc IT Security, IEEE Senior Member

20 questionsDomain: Containerized AI Workloads

Practice 10 questions Browse domain →

What the exam tests

What to know about Containerized AI Workloads

Be able to configure ACR scanning, Container Apps external ingress, and AKS resource and scheduling settings from manifests. The most important thing is choosing the correct Kubernetes field or Azure setting for the stated availability, security, or resource goal.

Enabling Microsoft Defender for Containers or ACR image scanning to detect vulnerabilities on push

Configuring Azure Container Apps ingress with external access and HTTPS/TLS termination settings

Setting Kubernetes CPU requests and limits in a pod or container resource specification

Using pod anti-affinity or topology spread constraints to distribute pods across availability zones

Watch out for

Common Containerized AI Workloads exam traps

▸Confusing image scanning with runtime threat protection; scanning happens at push or pull, not continuously inside a running container.
▸Setting only CPU limits without requests, which can cause scheduling failures or unexpected throttling under load.
▸Using pod affinity instead of anti-affinity, which co-locates pods and defeats the goal of spreading across fault domains.

Practice set

Containerized AI Workloads questions

20 questions · select your answer, then reveal the explanation

Question 1hardmultiple choice

Read the full Containerized AI Workloads explanation →

You are configuring an Azure Container Apps environment with a custom Virtual Network. Your AI containers need to securely connect to an Azure SQL Database that is secured behind a private endpoint. Which configuration is required on the Container Apps environment?

Trap 1: Use an external Azure Application Gateway in front of the container…

While Application Gateway handles inbound traffic, it does not resolve outbound private endpoint routing for the app environment.

Trap 2: Enable Azure Bastion on the subnet

Azure Bastion is used for interactive administrative RDP/SSH access to VMs, not container routing.

Trap 3: Configure IP restriction rules on the ingress controller

Ingress rules control incoming traffic, not outbound traffic to internal private endpoints.

Study all Containerized AI Workloads common traps →

A
Use an external Azure Application Gateway in front of the container apps
Why it fails: While Application Gateway handles inbound traffic, it does not resolve outbound private endpoint routing for the app environment.
B
Deploy the Container Apps environment into a custom VNet with workload profile subnets
Deploying the environment into a custom VNet with workload profile subnets gives containers VNet-integrated outbound connectivity, allowing private endpoint resolution to the Azure SQL Database. Without VNet injection, traffic egresses publicly and the private endpoint is unreachable.
C
Enable Azure Bastion on the subnet
Why it fails: Azure Bastion is used for interactive administrative RDP/SSH access to VMs, not container routing.
D
Configure IP restriction rules on the ingress controller
Why it fails: Ingress rules control incoming traffic, not outbound traffic to internal private endpoints.

Containerized AI Workloads practice questions

What to know about Containerized AI Workloads

Common Containerized AI Workloads exam traps

Containerized AI Workloads questions

You are configuring an Azure Container Apps environment with a custom Virtual Network. Your AI containers need to securely connect to an Azure SQL Database that is secured behind a private endpoint. Which configuration is required on the Container Apps environment?

You are deploying a Python Flask API that wraps an ONNX runtime model to Azure Container Instances (ACI). The container needs to expose port 5000 externally. Which parameter must you specify when creating the container group?

You have an AI model container that takes 10 seconds to load weights into memory upon startup. Users report HTTP 503 errors immediately after deployment because traffic is routed to the container before it is ready. Which probe should you configure?

You are managing an AKS cluster and need to ensure that GPU driver updates do not disrupt running AI inference workloads. Which AKS feature helps manage GPU operator lifecycle and driver installation?

You are scaling an AI workload in Azure Container Apps. Which TWO scale rule triggers are natively supported without custom KEDA extensions?

You are optimizing resource allocation for a GPU-backed AI model deployment on AKS. Which THREE Kubernetes concepts or objects are essential for managing GPU resources effectively?

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

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?

You manage an AKS cluster running high-throughput AI inference pods. During traffic spikes, pods experience latency due to slow container image pulls from Azure Container Registry (ACR). You want to optimize image pull performance across cluster nodes. Which feature should you enable?

You are designing a high-performance AI inference architecture on Azure Kubernetes Service (AKS). Which THREE AKS features or configurations should you incorporate to optimize performance and resource utilization? (Choose three.)

You are troubleshooting a containerized Python application in an Azure Container App that fails to respond to incoming HTTP requests. Which TWO diagnostic tools or features can you use within Azure Container Apps to investigate the issue? (Choose two.)

You are deploying a custom PyTorch inference model container to Azure Container Apps. The application requires GPU acceleration for real-time video processing. Which Azure Container Apps environment configuration tier must you select to support this requirement?

You are deploying a custom PyTorch model to Azure Container Apps. You need to ensure that the container utilizes GPU acceleration. Which configuration step is required in the Container App environment?

You need to automate the deployment of containerized AI models whenever a new image is pushed to ACR. What is the most efficient Azure-native tool for this trigger?

You are using Azure Container Apps to host a web API for an AI model. You want to ensure that only authorized traffic reaches the container. How should you secure the endpoint?

You are running a distributed AI training job on AKS using MPI. Which network configuration is critical for performance?

You are deploying an AI model to AKS that requires a specific kernel module. What is the recommended strategy to ensure the node has this module?

You have an AI model container that is frequently crashing due to OOM (Out of Memory) errors. How do you identify the actual memory usage compared to the limits?

Track your progress over time

Start a Containerized AI Workloads only practice session

Related AI-200 topic practice pages

Security And Observability practice questions

Event Driven Integration practice questions

Data Management Services And Vector Search practice questions

Containerized AI Workloads practice questions

AI-200 fundamentals practice questions

AI-200 scenario practice questions

AI-200 troubleshooting practice questions

Frequently asked questions

Track your progress

Study resources

Exam traps to avoid