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AI-300 · domain

Mlops Infrastructure

This domain covers the infrastructure layer of Azure Machine Learning: workspaces, compute, datastores, environments, and containerized job execution. Questions present operational scenarios—debugging a failing training container, choosing compute, or wiring pipeline components—and ask you to select the correct Azure ML resource, configuration, or troubleshooting approach.

39 questions14 easy13 medium12 hard

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What this domain covers

What to know about Mlops Infrastructure

You must be able to configure Azure ML compute, datastores, and environments, then diagnose containerized training failures using logs and direct image inspection. The single most important thing: know which resource—compute, datastore, or environment—owns each setting in a job or pipeline definition.

Selecting and configuring Azure ML compute clusters, instances, and attached compute for training and inference

Using datastores to abstract Azure Blob, File, and Data Lake storage from training scripts

Defining Azure ML environments with Conda dependencies, pip packages, and base Docker images

Debugging containerized jobs via logs, docker inspect, and interactive shell access to the training image

Watch out for

Common Mlops Infrastructure exam traps

  • ▸Confusing datastores with datasets: datastores are storage connection abstractions, not versioned data assets.
  • ▸Assuming the environment is set on the pipeline instead of on the component or job that needs it.
  • ▸Trying to debug a failed container only from the studio UI instead of inspecting logs and the image directly.

Question index

All Mlops Infrastructure questions (39)

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1

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

Easy
2

You are setting up an Azure Machine Learning workspace that must support reproducible training jobs. You need to ensure that the same code, dependencies, and data are used every time a job is rerun. Which two actions should you take? (Choose two.)

Medium
3

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?

Hard
4

Which TWO of the following can be used to manage Azure ML assets like environments and models?

Medium
5

In Azure ML, what is a 'Component'?

Easy
6

Which TWO of the following are benefits of using Azure ML Environments?

Easy
7

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?

Medium
8

You need to orchestrate a series of ML steps (Data prep, Training, Evaluation). Which Azure ML feature is specifically designed for this?

Medium
9

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?

Easy
10

You are designing a reusable Azure ML pipeline that must run a data validation step, a training step, and a registration step. The pipeline will be executed repeatedly with different input datasets, and you need each step to run in its own isolated environment with pinned dependencies. You also need the pipeline to be versioned and shareable across workspaces. What should you use to define the pipeline?

Hard
11

What is the purpose of the Azure ML 'Model Registry'?

Easy
12

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

Easy
13

Which TWO of the following storage types can be registered as an Azure ML Datastore?

Easy
14

You are configuring a real-time managed online endpoint in Azure Machine Learning. The model must be updated frequently with minimal downtime, and you need the ability to roll back quickly if a new version performs poorly. Which deployment strategy should you use?

Easy
15

Which THREE of the following are types of Azure ML endpoints?

Easy
16

You are experiencing latency issues with a model deployed on a Managed Online Endpoint. What is the first thing you should check?

Hard
17

Which TWO of the following are benefits of using the Azure ML CLI v2 for your MLOps pipelines?

Medium
18

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?

Easy
19

You are using GitHub Actions. You want to authenticate to Azure without using hardcoded credentials. What should you use?

Medium
20

You want to track your model experiments and compare their performance metrics. Which Azure ML feature provides this capability?

Medium
21

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

Easy
22

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?

Medium
23

Which THREE of the following are key components of a robust MLOps strategy in Azure?

Hard
24

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

Medium
25

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?

Hard
26

Which TWO of the following are required to secure an Azure ML workspace using a Private Link?

Hard
27

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?

Hard
28

You need to prevent data egress from your Azure ML environment. What configuration is required?

Hard
29

What is the primary benefit of using Azure ML compute clusters instead of compute instances for training?

Easy
30

You need to debug a training job that is failing inside a specific Docker container. What is the best way to investigate?

Hard
31

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

Easy
32

A pipeline step fails because it cannot find a file in the datastore. What is the most likely cause?

Hard
33

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?

Medium
34

Which THREE of the following are valid compute targets for Azure Machine Learning training?

Easy
35

You are preparing an Azure Machine Learning training job that must read a large Parquet dataset stored in an Azure Data Lake Storage Gen2 account. The job runs on an Azure ML compute cluster, and you want the data to be streamed directly from the storage account without first downloading the full dataset to the compute node's local disk. You also need to avoid storing account keys in the job script. Which Azure ML datastore configuration should you use?

Medium
36

Which THREE of the following represent lifecycle stages of an ML model in Azure ML?

Medium
37

Which THREE of the following are common reasons for a model deployment to fail on a Managed Online Endpoint?

Hard
38

Which THREE factors influence the cost of an Azure ML Compute Cluster?

Medium
39

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?

Hard

Frequently asked questions

What does the Mlops Infrastructure domain cover on the AI-300 exam?
You must be able to configure Azure ML compute, datastores, and environments, then diagnose containerized training failures using logs and direct image inspection. The single most important thing: know which resource—compute, datastore, or environment—owns each setting in a job or pipeline definition.
How many questions are in this domain?
This page lists all 39 Mlops Infrastructure questions in the AI-300 question bank. The actual exam draws from this domain proportionally to its weighting in the official exam blueprint.
What is the best way to practise this domain?
Start with a short focused session (10 questions) to identify gaps, then work through explanations. Repeat with a longer session once the weak areas feel solid.
Can I practise only Mlops Infrastructure questions?
Yes — the session launcher on this page filters questions to this domain only. Choose any session length for inline explanations and scoring.
Microsoft Certified: Machine Learning Operations Engineer Associate (AI-300) (AI-300) Mlops Infrastructure Practice Questions