Question

Difficulty: MediumScale Azure App Service Web Apps

You manage an Azure App Service Web App named RetailCartService that is currently hosted on a Free (F1) App Service plan. You need to implement and test CPU-based autoscaling for the application. You must ensure the application scales out to multiple instances under high load and scales back in when load decreases.

Which of the following represents the correct sequence of steps to configure and verify this autoscale behavior?

  1. 1Scale up the App Service plan from the Free (F1) tier to the Standard (S1) tier.
  2. 2Enable custom autoscale on the App Service plan and define both the scale-out and scale-in metric rules.
  3. 3Generate synthetic CPU load on the Web App to exceed the configured scale-out threshold.
  4. 4Monitor the App Service plan instance count to confirm it has successfully increased.

Answer

The correct sequence of steps starts with scaling up the App Service plan to the Standard tier, followed by enabling custom autoscale and defining the scaling rules. Next, synthetic load is generated to trigger the scale-out rule, and finally, the instance count is monitored to confirm the scale-out occurred.
The correct sequence begins with upgrading the App Service plan because scaling out and custom autoscale rules are not supported on the Free (F1) tier. Once scaled to the Standard (S1) tier, custom autoscale rules can be configured. To verify the configuration, synthetic load must be generated to trigger the scale-out threshold, and then the instance count is monitored to confirm the scale-out event succeeded.

Step-by-Step Solution

1
Scale up the hosting plan.
The App Service plan is upgraded from the Free (F1) tier to the Standard (S1) tier.
Free and Shared tiers do not support custom autoscale or scale-out capabilities. Standard (S) or Premium (P) tiers are required.
2
Configure the autoscale rules.
Custom autoscale is enabled with CPU-based scale-out and scale-in rules.
This establishes the autoscale profile and thresholds that govern the scale-out and scale-in operations.
3
Trigger the scale-out condition.
CPU utilization on the Web App increases beyond the scale-out threshold.
Synthetic load must be applied to simulate peak traffic and evaluate whether the autoscale engine detects the metric threshold breach.
4
Verify the scale-out outcome.
The App Service plan scales out to additional instances.
Monitoring the instance count confirms that the autoscale engine executed the rule and added capacity successfully.

Key Concept

Autoscaling configuration and verification workflow for Azure App Service Web Apps.
Estimated Time:1m 30s
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