AZ-204 Develop Azure compute solutions Practice Question
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?
⚠ Common exam trap
Watch out — 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.
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.
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.
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
Configuring authentication for a scaling endpoint is not relevant for Azure App Service autoscaling. The Azure platform's internal scaling engine directly monitors application metrics and automatically adjusts instance counts based on predefined rules, without exposing a user-facing endpoint that requires explicit authentication. This process is managed entirely within the Azure control plane, ensuring secure and autonomous scaling operations.
- ✗
Set the minimum and maximum instance count.
Why it's wrong here
While minimum and maximum instance counts define the boundaries within which an Azure App Service can scale, they do not directly set the current instance count. Autoscaling dynamically adjusts the number of instances between these limits based on configured scale-out and scale-in rules, which evaluate performance metrics. Therefore, merely setting these limits does not trigger or manage the actual scaling events.
- ✗
Set the Always On setting to On.
Why it's wrong here
The 'Always On' setting in Azure App Service ensures that the application remains loaded and responsive, preventing it from going idle due to inactivity and avoiding cold starts. However, this setting does not influence the number of instances running or the autoscaling logic. Its purpose is solely to maintain application availability, not to scale resources up or down based on demand.
- ✓
Configure a scale in condition based on CPU percentage.
Why this is correct
Configuring a scale-in condition based on CPU percentage is a fundamental aspect of optimizing resource utilization for an Azure App Service. This rule specifies that when the average CPU utilization across all instances drops below a defined threshold (e.g., 20%) for a sustained period, the autoscaling engine should reduce the number of active instances. This action helps to minimize operational costs during periods of low demand by releasing unnecessary resources.
- ✓
Configure a scale out condition based on CPU percentage.
Why this is correct
Configuring a scale-out condition based on CPU percentage is essential for ensuring application responsiveness during periods of increased demand for an Azure App Service. This rule dictates that if the average CPU utilization across all instances exceeds a specified threshold (e.g., 70%) for a set duration, the autoscaling engine should add more instances. This proactive measure helps distribute the load, preventing performance degradation and maintaining a positive user experience.
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