AZ-204 Develop Azure compute solutions Practice Question
Your organization runs a critical e-commerce application on Azure App Service. The application uses a Standard App Service plan with three instances. During a flash sale, traffic spikes cause some requests to fail with HTTP 503 errors. The operations team reports that the app's CPU usage reaches 95% during spikes. You need to ensure the application remains responsive without manual intervention. The solution must minimize cost while handling unpredictable traffic patterns. You evaluate the following options: A) Enable autoscale to scale out based on CPU usage threshold of 70%, with a maximum of 10 instances. B) Change the App Service plan to Premium v3 and enable zone redundancy. C) Implement a queue-based load leveling pattern using Azure Queue Storage and a background process. D) Use Azure Front Door with a Web Application Firewall (WAF) policy to distribute traffic. Which option should you recommend?
⚠ Common exam trap
Test-takers frequently confuse traffic distribution solutions (like Azure Front Door) with scaling solutions, or assume that upgrading the plan is necessary for high availability, when autoscale on the existing Standard plan is the most cost-effective and direct fix for CPU-driven 503 errors.
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
✓
Enable autoscale to scale out based on CPU usage threshold of 70%, with a maximum of 10 instances.
Enabling autoscale on the Standard App Service plan allows the application to automatically scale out from 3 to up to 10 instances when CPU exceeds 70%, handling traffic spikes without manual intervention. This minimizes cost by only adding instances when needed, and the Standard plan supports autoscale natively, making it the most cost-effective solution for unpredictable traffic patterns.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Azure Front Door with a Web Application Firewall (WAF) policy to distribute traffic.
Why it's wrong here
Azure Front Door acts as a global load balancer and CDN, providing features like Web Application Firewall (WAF) for security and content caching for performance. While it efficiently distributes incoming traffic across backend resources, it does not inherently increase the compute capacity of the application's backend instances. Front Door can direct traffic to available instances but does not perform the dynamic scaling out of those instances to handle increased load.
- ✓
Enable autoscale to scale out based on CPU usage threshold of 70%, with a maximum of 10 instances.
Why this is correct
Enabling autoscale directly addresses the need for dynamic compute capacity by automatically adding or removing instances based on defined metrics. Setting a CPU usage threshold of 70% ensures that new instances are provisioned proactively when demand increases, while the maximum of 10 instances prevents unbounded scaling. This approach effectively handles traffic spikes by scaling out horizontally, optimizing both performance and cost efficiency.
- ✗
Implement a queue-based load leveling pattern using Azure Queue Storage and a background process.
Why it's wrong here
Implementing a queue-based load leveling pattern using Azure Queue Storage is effective for decoupling components and handling asynchronous tasks. However, for a critical e-commerce application requiring immediate responses to user requests, this pattern introduces latency by shifting processing to a background worker. It does not provide the immediate, synchronous scaling of front-end compute resources needed to directly handle a sudden surge in interactive user traffic.
- ✗
Change the App Service plan to Premium v3 and enable zone redundancy.
Why it's wrong here
Changing the App Service plan to Premium v3 provides more powerful underlying virtual machines and enables features like zone redundancy for higher availability. While this offers vertical scaling (scaling up) and improved resilience, it does not automatically scale out the number of instances based on real-time demand. This approach would result in higher fixed costs without the dynamic capacity adjustment required to efficiently manage fluctuating traffic spikes.
Go deeper
Related to this question
Learn chapter
Azure Functions Development
Key term
Azure Queue Storage
Azure Queue Storage is a cloud service for storing and retrieving large numbers of messages that can be accessed from anywhere, enabling asynchronous communication between application components.
Key term
Azure App Service Plans
An Azure App Service Plan defines the compute resources, pricing tier, scaling capabilities, and region for one or more web apps, API apps, mobile app backends, or Azure Functions hosted in Azure App Service.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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