- A
An availability set with manual VM resizing.
Why wrong: Manual resizing does not provide automatic scaling and would require operator intervention during every demand change.
- B
A virtual machine scale set with autoscale rules.
A virtual machine scale set is built for identical compute instances that need to scale horizontally. Autoscale rules can watch CPU, adjust the instance count automatically, and maintain the minimum and maximum capacity you define. This fits stateless services very well because any instance can handle incoming requests once traffic is distributed across the set.
- C
A single Standard D-series VM with scheduled shutdown.
Why wrong: A single VM cannot scale out horizontally and would become a bottleneck under the stated load changes.
- D
A load balancer in front of two unmanaged VMs.
Why wrong: A load balancer distributes traffic, but it does not create or remove instances when demand changes.
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.
A stateless Linux API should start with 2 instances, scale out to 6 when average CPU stays above 75 percent for 10 minutes, and scale back in when load drops. Which Azure compute resource should the administrator deploy?
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
A virtual machine scale set with autoscale rules.
A virtual machine scale set (VMSS) with autoscale rules is the correct choice because it natively supports scaling out and scaling in based on performance metrics like average CPU percentage. The requirement for a stateless Linux API with a minimum of 2 instances, scaling to 6 when CPU exceeds 75% for 10 minutes, and scaling back in when load drops is exactly the use case VMSS is designed for. Autoscale rules can be configured to use a scale-out and scale-in policy with a cool-down period, ensuring the application remains responsive while optimizing cost.
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.
- ✗
An availability set with manual VM resizing.
Why it's wrong here
Manual resizing does not provide automatic scaling and would require operator intervention during every demand change.
- ✓
A virtual machine scale set with autoscale rules.
Why this is correct
A virtual machine scale set is built for identical compute instances that need to scale horizontally. Autoscale rules can watch CPU, adjust the instance count automatically, and maintain the minimum and maximum capacity you define. This fits stateless services very well because any instance can handle incoming requests once traffic is distributed across the set.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
A single Standard D-series VM with scheduled shutdown.
Why it's wrong here
A single VM cannot scale out horizontally and would become a bottleneck under the stated load changes.
- ✗
A load balancer in front of two unmanaged VMs.
Why it's wrong here
A load balancer distributes traffic, but it does not create or remove instances when demand changes.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse an availability set with autoscaling, not realizing that availability sets only provide redundancy and fault tolerance, not dynamic scaling, or they may think a load balancer with two VMs is sufficient, overlooking the requirement for automatic scaling based on CPU thresholds.
Detailed technical explanation
How to think about this question
Azure VMSS autoscale uses Azure Monitor metrics and can be configured with a scale-out rule that triggers when the average CPU percentage exceeds 75% for a duration of 10 minutes (using the 'Average' statistic and a 10-minute time grain). The scale-in rule typically uses a lower threshold (e.g., 25%) to avoid flapping. VMSS also supports a 'scale-in policy' to control which instances are removed first (e.g., Default, NewestVM, or OldestVM), which is critical for stateless workloads to ensure graceful termination. The autoscale engine evaluates metrics every 1-5 minutes and applies a cool-down period (default 5 minutes) to prevent rapid oscillations.
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
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
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: A virtual machine scale set with autoscale rules. — A virtual machine scale set (VMSS) with autoscale rules is the correct choice because it natively supports scaling out and scaling in based on performance metrics like average CPU percentage. The requirement for a stateless Linux API with a minimum of 2 instances, scaling to 6 when CPU exceeds 75% for 10 minutes, and scaling back in when load drops is exactly the use case VMSS is designed for. Autoscale rules can be configured to use a scale-out and scale-in policy with a cool-down period, ensuring the application remains responsive while optimizing cost.
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
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Last reviewed: Jun 11, 2026
This AZ-104 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AZ-104 exam.
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