- A
Use a virtual machine scale set for the identical application instances.
A VM scale set is the compute service built for multiple identical instances with centralized scaling and management. It is the correct foundation for a workload that expands and contracts over time.
- B
Create an autoscale profile with a scale-out rule based on average CPU utilization.
The autoscale profile is where the CPU threshold and evaluation window are defined. A scale-out rule tied to average CPU above 70 percent for 10 minutes matches the business requirement precisely.
- C
Set minimum and maximum instance counts so the service cannot scale below 3 or above 8.
Minimum and maximum bounds keep autoscale within the required operating range. They prevent over-scaling costs and ensure the service always keeps at least the minimum capacity online.
- D
Place the VMs in an availability set instead of using a scale set.
Why wrong: An availability set improves resilience, but it does not provide built-in horizontal autoscaling. It would not meet the requirement to add and remove instances automatically based on CPU usage.
- E
Clone the VM manually whenever CPU rises and remove clones by hand later.
Why wrong: Manual cloning is slow, error-prone, and defeats the goal of automatic scaling. It also makes it harder to maintain identical configuration across instances over time.
AZ-104 Deploy and Manage Azure Compute Practice Question
This AZ-104 practice question tests your understanding of deploy and manage azure compute. 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.
The operations team wants 3 to 8 identical Linux VM instances, with more instances added when average CPU stays above 70 percent for 10 minutes and removed when load falls. Which three settings should be configured? Select three.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Use a virtual machine scale set for the identical application instances.
A virtual machine scale set (VMSS) is the correct Azure service for deploying and managing a group of identical, load-balanced Linux VMs that can automatically scale in and out based on demand. It supports autoscaling rules that adjust the instance count within a defined range, meeting the requirement for 3 to 8 identical instances with automatic addition when average CPU exceeds 70% for 10 minutes and removal when load falls.
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.
- ✓
Use a virtual machine scale set for the identical application instances.
Why this is correct
A VM scale set is the compute service built for multiple identical instances with centralized scaling and management. It is the correct foundation for a workload that expands and contracts over time.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Create an autoscale profile with a scale-out rule based on average CPU utilization.
Why this is correct
The autoscale profile is where the CPU threshold and evaluation window are defined. A scale-out rule tied to average CPU above 70 percent for 10 minutes matches the business requirement precisely.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Set minimum and maximum instance counts so the service cannot scale below 3 or above 8.
Why this is correct
Minimum and maximum bounds keep autoscale within the required operating range. They prevent over-scaling costs and ensure the service always keeps at least the minimum capacity online.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Place the VMs in an availability set instead of using a scale set.
Why it's wrong here
An availability set improves resilience, but it does not provide built-in horizontal autoscaling. It would not meet the requirement to add and remove instances automatically based on CPU usage.
- ✗
Clone the VM manually whenever CPU rises and remove clones by hand later.
Why it's wrong here
Manual cloning is slow, error-prone, and defeats the goal of automatic scaling. It also makes it harder to maintain identical configuration across instances over time.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse availability sets with scale sets, thinking both provide scaling, but availability sets only offer redundancy and fault tolerance, not automatic scaling or instance count management.
Detailed technical explanation
How to think about this question
Azure VMSS uses an autoscale profile with metrics-based rules, where the scale-out rule triggers when the average CPU percentage across all instances exceeds 70% for a 10-minute duration (using the 'Average' statistic and a 10-minute time grain). The scale-in rule similarly reduces instances when CPU drops below a threshold, and the minimum and maximum instance counts (3 and 8) are enforced by the autoscale profile to prevent over- or under-provisioning. Under the hood, VMSS leverages Azure Monitor autoscale with a cooldown period (default 5 minutes) to avoid flapping, ensuring stability during scaling events.
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.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this AZ-104 question test?
Deploy and Manage Azure Compute — This question tests Deploy and Manage Azure Compute — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use a virtual machine scale set for the identical application instances. — A virtual machine scale set (VMSS) is the correct Azure service for deploying and managing a group of identical, load-balanced Linux VMs that can automatically scale in and out based on demand. It supports autoscaling rules that adjust the instance count within a defined range, meeting the requirement for 3 to 8 identical instances with automatic addition when average CPU exceeds 70% for 10 minutes and removal when load falls.
What should I do if I get this AZ-104 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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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Last reviewed: Jun 11, 2026
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