AZ-204 Practice Question: Monitor, troubleshoot, and optimize Azure solutions
Which TWO actions should you take to reduce the cost of an Azure App Service plan that is underutilized?
⚠ Common exam trap
A common mix-up: candidates confuse scaling out (adding instances) with scaling down (reducing tier), or think auto-scaling always saves money, when in fact it can increase costs if the base load is already low.
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
✓
Scale out to fewer instances
Scaling out to fewer instances directly reduces the number of VMs running the App Service plan, which lowers the compute cost. Since the plan is underutilized, fewer instances can handle the existing load without performance degradation, making this a cost-optimization action.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Deploy the application to a different region
Why it's wrong here
While Azure service pricing can vary by region, moving an application to a different region does not inherently guarantee cost reduction and could even increase costs due to data transfer fees, potential re-architecting, or higher prices in the target region for specific services. The fundamental cost structure of the App Service plan itself remains, with only regional price adjustments, which may not be substantial enough to offset the effort or other associated costs of migration. This action primarily addresses latency or compliance, not direct cost reduction for underutilization.
- ✗
Enable auto-scaling
Why it's wrong here
Enabling auto-scaling allows the App Service to dynamically adjust the number of instances based on demand. While auto-scaling can optimize costs by scaling in during periods of low demand, if the application is already underutilized and the auto-scaling rules are not precisely configured, it might maintain a higher minimum instance count or scale out unnecessarily, potentially increasing overall costs. Auto-scaling's primary goal is to ensure performance and availability, and it requires careful tuning to achieve cost savings for an already over-provisioned application.
- ✗
Purchase Reserved Instances
Why it's wrong here
Purchasing Azure Reserved Instances (RIs) offers significant discounts for committing to a specific resource type and region for one or three years. However, RIs are most effective for workloads with consistent and predictable usage. If an application is currently underutilized, purchasing RIs for its existing, over-provisioned configuration would lock in costs for resources that are not fully utilized, potentially leading to higher overall expenditure compared to first scaling down the resources to match actual demand. RIs are a cost optimization strategy for stable workloads, not a solution for addressing underutilization.
- ✓
Scale out to fewer instances
Why this is correct
"Scaling out" refers to adjusting the number of instances running within an App Service plan. If an application is underutilized, it means it has more instances than required to handle its current workload efficiently. Reducing the instance count directly decreases the total computational resources consumed by the application, as each instance incurs a cost. This action directly lowers the operational expenditure for the App Service plan by aligning the provisioned capacity more closely with the actual demand.
- ✓
Scale down the App Service plan to a lower tier
Why this is correct
"Scaling down" an App Service plan involves changing its pricing tier (e.g., from Standard to Basic) or its size within a tier (e.g., from P2V3 to P1V3). Lower tiers and smaller sizes provide fewer CPU, memory, and storage resources, along with potentially fewer features, but come at a significantly reduced monthly cost. If an application is underutilized, it likely does not require the extensive resources or advanced features of a higher-tier plan, making a transition to a more cost-effective tier a direct and impactful way to reduce monthly Azure expenditure.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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