The answer is Azure Virtual Machine Scale Sets (VMSS), because it is the only Azure service designed to automatically add or remove identical VM instances based on metrics like CPU utilization. When you configure an autoscale rule on a VMSS, it monitors the average CPU across the instance pool and triggers scale-out or scale-in actions, seamlessly integrating with an Azure Load Balancer to distribute traffic only to healthy, active VMs. On the AZ-305 exam, this scenario tests your understanding of scaling compute resources for high availability and elasticity—a common trap is confusing VMSS with Azure App Service autoscaling, but remember that VMSS is specifically for managing a fleet of VMs behind a load balancer. For a memory tip, think “VMSS = VM Scale Set = CPU scales the set,” reinforcing that CPU-based autoscaling is a core VMSS feature, not a standalone VM or availability set capability.
AZ-305 Design infrastructure solutions Practice Question
This AZ-305 practice question tests your understanding of design infrastructure solutions. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company runs a web application on Azure VMs in a single region. The application must scale out automatically based on CPU utilization. The VMs are behind an Azure Load Balancer. Which Azure service should they use to automatically add or remove VMs based on demand?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Azure Virtual Machine Scale Sets
Azure Virtual Machine Scale Sets (VMSS) is the correct service because it provides automatic scaling of identical VM instances based on metrics like CPU utilization. When you configure an autoscale rule on a VMSS, it automatically adds or removes VM instances behind the Azure Load Balancer, ensuring the application scales out or in based on demand without manual intervention.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✓
Azure Virtual Machine Scale Sets
Why this is correct
Correct: VMSS provides autoscaling based on metrics and integrates with Azure Load Balancer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Azure App Service
Why it's wrong here
Incorrect: Azure App Service is a PaaS service for web apps, not for managing VMs.
✗
Azure Functions
Why it's wrong here
Incorrect: Azure Functions is serverless compute for event-driven code, not for scaling VMs.
✗
Azure Batch
Why it's wrong here
Incorrect: Azure Batch is for running large-scale parallel compute jobs, not for web application autoscaling.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse Azure App Service's autoscale feature (which scales the number of App Service instances, not VMs) with the requirement to scale VMs behind a load balancer, leading them to select App Service instead of VMSS.
Detailed technical explanation
How to think about this question
Under the hood, VMSS uses an autoscale engine that evaluates CPU metrics (e.g., Percentage CPU > 75% for 5 minutes) and triggers scale-out operations by creating new VM instances from a configured image. The VMSS integrates directly with Azure Load Balancer via backend address pools, so new VMs are automatically added to the load balancer's distribution. A subtle behavior is that scale-in operations use a 'default' or 'NewestVM' deallocation policy, which can cause connection-draining issues if not configured with a custom policy.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this AZ-305 question in full detail.
Design infrastructure solutions — This question tests Design infrastructure solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Azure Virtual Machine Scale Sets — Azure Virtual Machine Scale Sets (VMSS) is the correct service because it provides automatic scaling of identical VM instances based on metrics like CPU utilization. When you configure an autoscale rule on a VMSS, it automatically adds or removes VM instances behind the Azure Load Balancer, ensuring the application scales out or in based on demand without manual intervention.
What should I do if I get this AZ-305 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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