AZ-204 Develop Azure compute solutions Practice Question
Your company has an Azure App Service web app that runs on a Standard App Service plan. You need to scale out the app to handle increased traffic during business hours and scale in during off-hours. What should you configure?
⚠ Common exam trap
Watch out — candidates often confuse 'scaling up' (increasing the plan tier or instance size) with 'scaling out' (increasing the number of instances), and assuming that manual scaling or Traffic Manager can achieve automatic scaling based on load.
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 autoscale rules on the App Service plan to scale out and in based on CPU usage.
Azure App Service autoscale rules allow you to automatically scale out (increase instance count) and scale in (decrease instance count) based on metrics like CPU usage. This meets the requirement to handle increased traffic during business hours and reduce costs during off-hours without manual intervention. Autoscale is configured at the App Service plan level, not the web app itself, and works with the Standard tier and above.
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 autoscale rules on the App Service plan to scale out and in based on CPU usage.
Why this is correct
Autoscale rules on the App Service plan provide the capability to automatically adjust the number of instances (scale out) when demand, such as CPU usage, exceeds a defined threshold, and scale in when demand decreases. This ensures the web app maintains optimal performance and availability under fluctuating loads without requiring manual intervention, making it the most efficient and automated solution for dynamic capacity management.
- ✗
Manually increase the instance count during business hours.
Why it's wrong here
Manually increasing the instance count during business hours requires constant human oversight and intervention to monitor application load and adjust resources accordingly. This approach is reactive, inefficient, and prone to delays, meaning the application might experience performance degradation during sudden spikes in traffic before a human can respond, failing to provide an automated solution.
- ✗
Scale up the App Service plan to a Premium plan.
Why it's wrong here
Scaling up the App Service plan involves increasing the computational resources (e.g., CPU, memory, storage) allocated to each individual instance, effectively making each server more powerful. While this can improve the performance of a single instance, it does not increase the *number* of instances available to distribute concurrent user requests, which is essential for handling high traffic volumes through horizontal scalability.
- ✗
Use Azure Traffic Manager to distribute load.
Why it's wrong here
Azure Traffic Manager is a DNS-based global load balancer that distributes incoming traffic across multiple endpoints, which can include App Service web apps, based on various routing methods. While it can direct users to the healthiest or closest endpoint, Traffic Manager itself does not dynamically scale the underlying App Service instances; it relies on the App Service plan's own scaling capabilities to manage the number of running instances.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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