AI-300 Mlops Infrastructure — Timed 15 Questions

Question 1

A data scientist needs to access data in an Azure Data Lake Storage Gen2 account from Azure ML. You need to ensure the workspace uses the most secure method to access this data. What should you configure?

15 minute time limit — choose an answer to begin.

Accepted Answer

User-Assigned Managed Identity. Using a User-Assigned Managed Identity allows the Azure ML workspace to authenticate with the storage account without storing keys.

Answer

Shared Key

Answer

Public Access

Answer

Account SAS

Question 2

You want to automate the deployment of a model using GitHub Actions. Which file format is standard for defining the Azure ML CLI v2 deployment configuration?

Accepted Answer

YAML. Azure ML CLI v2 uses YAML files to define configurations for jobs, endpoints, and deployments.

Answer

JSON

Answer

XML

Answer

Bicep

Question 3

You need to attach an existing Azure Kubernetes Service (AKS) cluster to your Azure ML workspace for model inference. Which credential type is required to establish this connection?

Accepted Answer

Service Principal. The Service Principal is the standard method for managing identity-based access for AKS clusters attached to Azure ML.

Answer

SAS Token

Answer

Managed Identity

Answer

Azure Active Directory B2C

Question 4

Your Azure ML training job fails with an 'Out of Memory' error on a GPU cluster. You need to ensure the job runs successfully without modifying the model code. What should you do?

Accepted Answer

Change the VM size to one with higher memory. Scaling up to a VM size with more RAM or GPU memory is the most direct way to resolve OOM issues in training jobs.

Answer

Increase the idle time for the compute cluster

Answer

Enable auto-scale to zero

Answer

Update the workspace storage account

Question 5

You are creating a CI/CD pipeline in Azure DevOps. Which extension is essential to integrate Azure ML tasks into your build/release pipeline?

Accepted Answer

Azure Machine Learning extension. The Azure Machine Learning extension provides the necessary tasks to interact with the Azure ML CLI from DevOps pipelines.

Answer

Visual Studio Code extension

Answer

Terraform extension

Answer

Kubernetes extension

Question 6

You are setting up an Azure Machine Learning workspace and need to ensure that the workspace is not accessible from the public internet. Which networking feature should you configure?

Accepted Answer

Private Endpoint. A Private Endpoint allows you to access your workspace securely via a private IP address within your virtual network.

Answer

Azure Bastion

Answer

Application Gateway

Answer

Service Tags

Question 7

You need to monitor the health of your deployed Azure ML models. Which service is integrated directly with Azure ML to provide automated metrics and logging?

Accepted Answer

Azure Application Insights. Azure Application Insights is the native service for monitoring logs, metrics, and telemetry from deployed model endpoints.

Answer

Azure Event Grid

Answer

Azure Policy

Answer

Azure Data Factory

Question 8

Which component in an Azure ML pipeline definition is responsible for specifying the runtime environment, including Python packages and Conda dependencies?

Accepted Answer

Environment. The Environment object defines the software stack, including dependencies and Docker images, needed for a job.

Answer

Compute Target

Answer

Datastore

Answer

Component

Question 9

What is the primary function of an Azure ML 'Datastore'?

Accepted Answer

Connection to storage services. Datastores are abstractions to securely connect to underlying data storage services like Blob storage or Data Lake.

Answer

Experiment tracking

Answer

Model registry

Answer

Compute resource management

Question 10

Which Azure feature is used to define infrastructure as code for your Azure ML workspace?

Accepted Answer

Azure Bicep. Azure Bicep is the recommended tool for defining and deploying Azure resources as code.

Answer

Azure Portal

Answer

PowerShell

Answer

Azure CLI

Question 11

You are managing a multi-workspace environment. You need to restrict the ability to create new compute clusters to only specific users. Where should you apply this control?

Accepted Answer

Azure RBAC on the Workspace. RBAC (Role-Based Access Control) at the workspace level determines which users can interact with compute resources.

Answer

Network Security Group

Answer

Azure Storage Access Policies

Answer

Azure ML Datastore configuration

Question 12

You need to ensure that a training script running on Azure ML has access to secrets (like API keys) without hardcoding them in the script. What should you use?

Accepted Answer

Azure Key Vault. Azure Key Vault is integrated with Azure ML to securely manage and inject secrets into training jobs.

Answer

Environment variables in the Dockerfile

Answer

Local configuration files

Answer

Hardcoding in the script

Question 13

Your team uses a custom Docker image for training. You need to update the image in the Azure Container Registry (ACR). What is the recommended workflow to ensure Azure ML picks up the latest version?

Accepted Answer

Update the image tag and refresh the Environment. Updating the image tag and updating the environment definition in Azure ML forces the system to pull the new version.

Answer

Modify the storage account permissions

Answer

Restart the compute cluster

Answer

Delete and recreate the workspace

Question 14

When configuring a compute instance, which setting allows you to automatically stop the instance during periods of inactivity?

Accepted Answer

Idle shutdown. Idle shutdown automatically turns off the compute instance when no active processes are detected, saving costs.

Answer

Provisioning timeout

Answer

Auto-scaling

Answer

Priority based scheduling

Question 15

You are deploying a model as a real-time endpoint. You want to ensure the deployment can handle sudden spikes in traffic. Which scaling configuration should you enable?

Accepted Answer

Auto-scaling. Auto-scaling allows the endpoint to dynamically adjust node count based on CPU/Memory usage.

Answer

Static node count

Answer

Batch deployment

Answer

Pre-warmed instances

Answer

None of the above