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AI-300 · domain

Genaiops Infrastructure

This domain covers the infrastructure that keeps GenAI workloads running on Azure: provisioning and scaling model deployments, authenticating to Azure AI Foundry projects, monitoring and evaluating deployed models, and auditing model access across an organization. Questions are scenario-based, asking you to pick the most effective Azure-native fix for throttling, access, evaluation, or compliance problems.

45 questions10 easy22 medium13 hard

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What this domain covers

What to know about Genaiops Infrastructure

Be able to diagnose and fix GenAI infrastructure issues in Azure: scale model deployments to stop throttling, choose Entra ID or managed identity authentication for AI Foundry projects, run built-in evaluations, and route model access logs to Azure Monitor for auditing.

Scaling model-as-a-service deployments and handling throttling with Azure AI Foundry quota and capacity settings

Authenticating to Azure AI Foundry projects using Microsoft Entra ID, managed identities, and API keys

Using Azure AI Foundry evaluation features to measure model performance with built-in metrics

Auditing model access logs with Azure Monitor, diagnostic settings, and Log Analytics workspaces

Watch out for

Common Genaiops Infrastructure exam traps

  • ▸Assuming throttling is fixed by retrying or prompt changes instead of increasing deployment capacity or quota in Azure AI Foundry.
  • ▸Treating API keys as the preferred auth method when Microsoft Entra ID and managed identities are the recommended, more secure options.
  • ▸Believing evaluation requires external tooling rather than Azure AI Foundry's built-in evaluators and metrics.

Question index

All Genaiops Infrastructure questions (45)

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1

You are monitoring the cost of your GenAI infrastructure. You want to track usage per specific project. Which feature in Azure AI Foundry should you use?

Easy
2

You are setting up a CI/CD pipeline for GenAI models. You need to evaluate the model's performance on a benchmark dataset before it is promoted to the production endpoint. Which Azure AI Foundry capability should be integrated into your pipeline?

Medium
3

Which THREE features does Azure AI Foundry provide to help developers?

Medium
4

Your team is using Semantic Kernel for agent orchestration. You notice frequent transient errors when the agent interacts with multiple LLM services. How should you implement infrastructure-level resiliency?

Hard
5

You are deploying a model that requires specific GPUs. How do you ensure you get the right infrastructure?

Medium
6

You want to automate the scaling of your AI agent orchestration. Which TWO components do you need to configure?

Medium
7

Which THREE metrics are critical for monitoring the health of a GenAI deployment?

Hard
8

What is the benefit of using 'Model Catalog' in Azure AI Foundry?

Easy
9

Your team runs a GenAI agent in Azure AI Foundry that calls an Azure OpenAI model deployment. The agent intermittently fails with authentication errors, and you suspect the managed identity used by the agent's compute does not have the required role assignment on the Azure AI Foundry resource. You need to verify and fix the role assignment. Which action should you take?

Medium
10

What is the purpose of a 'System-Assigned Managed Identity' in the context of an Azure AI project?

Medium
11

You are troubleshooting high latency in a RAG-based application. The vector search is fast, but the generation phase is slow. Which component should be scaled?

Hard
12

Which THREE items should you keep track of in your AI Foundry project to ensure good governance?

Easy
13

You have a sudden spike in requests. What is the quickest way to check if you have hit your Azure OpenAI token quota?

Medium
14

You are deploying a large model. During the deployment, you encounter a 'Resource Not Available' error. What is the most likely cause?

Hard
15

You need to ensure that your LLM responses are filtered for harmful content. Which infrastructure component provides this capability?

Medium
16

When sharing an AI project with a team, which resource group architecture is best practice for lifecycle management?

Easy
17

You are experiencing throttling on your AI endpoint. Which TWO steps should you take?

Hard
18

Where do you define the model deployment settings, including instance count and version?

Easy
19

You manage a GenAI application in Azure AI Foundry that uses a provisioned throughput deployment for a large language model. Finance asks you to reduce cost during off-peak hours without affecting peak-hour performance. The deployment currently runs at a fixed provisioned capacity around the clock. Which approach should you use?

Hard
20

You are troubleshooting a failed agent deployment. Which TWO areas should you inspect first?

Hard
21

To optimize the cost of your AI infrastructure, which THREE actions should you consider?

Hard
22

Which Azure feature should you use to restrict traffic to your AI Foundry project to specific IP addresses?

Medium
23

You need to update a prompt flow without downtime. What deployment strategy should you use?

Medium
24

You need to audit all model access logs across your organization. What is the most effective approach?

Medium
25

An agent orchestration system is timing out because it waits too long for tool output. How can you optimize the infrastructure handling of tool calls?

Hard
26

You are automating the deployment of your AI project. What is the recommended tool to manage infrastructure-as-code (IaC) for Azure AI Foundry?

Hard
27

You are configuring a connection to a vector store. What is the best way to handle the secret credential?

Hard
28

Which THREE of the following are components of an Azure AI Foundry project?

Easy
29

Your team wants to use prompt versioning. Where should this be managed in the AI Foundry workflow?

Medium
30

You are designing the infrastructure for a multi-agent system. Which THREE of the following are essential components to ensure agent orchestration scalability?

Medium
31

A team is scaling a GenAI application that utilizes multiple models via model-as-a-service. You notice that inference requests are being throttled. What is the most effective infrastructure-level adjustment to handle the increased load?

Medium
32

You are planning a production GenAI deployment. Which THREE of the following are necessary infrastructure considerations?

Medium
33

You are building a RAG application. Where should you store the indexed documents for optimal retrieval performance?

Medium
34

Which TWO of the following are valid ways to authenticate to an Azure AI Foundry project?

Easy
35

Which Azure AI Foundry feature allows you to evaluate your model's performance?

Easy
36

What is the recommended approach for managing configuration settings for different environments (Dev, Test, Prod) in an AI application?

Medium
37

Which TWO of the following are benefits of using Prompt Flow for orchestration?

Medium
38

A developer is troubleshooting an agent that is failing to connect to an external tool. Which THREE of the following infrastructure settings should be verified?

Medium
39

You are onboarding a team to Azure AI Foundry. You need to assign the minimum permissions for a developer to deploy and test a model. Which role should you assign?

Easy
40

You are implementing an agentic workflow using Azure AI Foundry. The agent needs to access a secure external API. How should you store the API key securely within the project?

Hard
41

Your team wants to monitor the safety of model outputs. Which THREE steps should you take?

Medium
42

You want to automate the testing of your prompt flows as part of your CI/CD pipeline. Which tool should you use?

Medium
43

You notice your model deployment status is 'Succeeded' but inference requests are failing. Where should you first check for connectivity issues?

Easy
44

You need to monitor the 'latency' and 'token usage' of your model deployments in real-time. Which tool provides the most granular view?

Hard
45

What is the primary function of the 'Prompt Flow' tool within Azure AI Foundry?

Medium

Frequently asked questions

What does the Genaiops Infrastructure domain cover on the AI-300 exam?
Be able to diagnose and fix GenAI infrastructure issues in Azure: scale model deployments to stop throttling, choose Entra ID or managed identity authentication for AI Foundry projects, run built-in evaluations, and route model access logs to Azure Monitor for auditing.
How many questions are in this domain?
This page lists all 45 Genaiops 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 Genaiops 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) Genaiops Infrastructure Practice Questions