- A
Configure authentication for the scaling endpoint.
Why wrong: Authentication is not required for autoscaling.
- B
Set the minimum and maximum instance count.
Why wrong: Instance count is set by the scaling rules, not directly.
- C
Set the Always On setting to On.
Why wrong: Always On prevents the app from going idle, but it does not affect scaling.
- D
Configure a scale in condition based on CPU percentage.
Scale in condition triggers when CPU drops below a threshold.
- E
Configure a scale out condition based on CPU percentage.
Scale out condition triggers when CPU exceeds a threshold.
AZ-204 Develop Azure compute solutions Practice Question
This AZ-204 practice question tests your understanding of develop azure compute 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.
You are developing a web application that will be deployed to Azure App Service. You need to configure automatic scaling based on CPU usage. Which TWO settings should you configure?
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
Configure a scale in condition based on CPU percentage.
Option D is correct because configuring a scale-in condition based on CPU percentage allows the App Service plan to automatically reduce the number of instances when CPU usage drops below a defined threshold, which is essential for cost optimization. Option E is correct because configuring a scale-out condition based on CPU percentage enables the platform to automatically add instances when CPU usage exceeds a threshold, ensuring the application can handle increased load. Together, these two settings define the autoscale rules that react to CPU metrics, which is the core requirement for CPU-based automatic scaling.
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.
- ✗
Configure authentication for the scaling endpoint.
Why it's wrong here
Authentication is not required for autoscaling.
- ✗
Set the minimum and maximum instance count.
Why it's wrong here
Instance count is set by the scaling rules, not directly.
- ✗
Set the Always On setting to On.
Why it's wrong here
Always On prevents the app from going idle, but it does not affect scaling.
- ✓
Configure a scale in condition based on CPU percentage.
Why this is correct
Scale in condition triggers when CPU drops below a threshold.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Configure a scale out condition based on CPU percentage.
Why this is correct
Scale out condition triggers when CPU exceeds a threshold.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse the prerequisite settings (like instance count limits) with the actual scaling condition rules, or they think that only one direction (scale-out or scale-in) is needed, but autoscale requires both to be fully defined for CPU-based scaling to work correctly.
Detailed technical explanation
How to think about this question
Azure App Service autoscale uses Azure Monitor metrics (e.g., CPU percentage) and applies a rule-based engine that evaluates the metric over a specified duration (e.g., 10 minutes) before triggering a scale action. The scale-out and scale-in conditions are defined separately to allow asymmetric thresholds (e.g., scale out at 70% CPU, scale in at 30% CPU) to prevent flapping. In a real-world scenario, you might also configure a cool-down period (e.g., 5 minutes) after a scale action to avoid 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.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this AZ-204 question test?
Develop Azure compute solutions — This question tests Develop Azure compute solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Configure a scale in condition based on CPU percentage. — Option D is correct because configuring a scale-in condition based on CPU percentage allows the App Service plan to automatically reduce the number of instances when CPU usage drops below a defined threshold, which is essential for cost optimization. Option E is correct because configuring a scale-out condition based on CPU percentage enables the platform to automatically add instances when CPU usage exceeds a threshold, ensuring the application can handle increased load. Together, these two settings define the autoscale rules that react to CPU metrics, which is the core requirement for CPU-based automatic scaling.
What should I do if I get this AZ-204 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 24, 2026
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