SOA-C02 Cost and Performance Optimization Practice Question
A company is running a production web application on EC2 instances behind an ALB. The application experiences predictable traffic spikes during business hours. Which cost optimization strategy would be MOST effective?
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 Scheduled Scaling to add instances before the spike and remove after.
The most effective cost optimization strategy because Scheduled Scaling allows you to increase capacity predictably before traffic spikes and decrease afterward, ensuring you only pay for what you need. Option B is incorrect because Spot Instances can be interrupted and are not suitable for production workloads that require high availability. Option C is incorrect because using larger instances does not dynamically adjust to spikes and may lead to over-provisioning during low traffic. Option D is incorrect because On-Demand instances are more expensive than using scheduled scaling with a mix of Reserved Instances or Savings Plans to cover the baseline and scheduled scaling for the spikes.
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 Scheduled Scaling to add instances before the spike and remove after.
Why this is correct
Configure Scheduled Scaling to add instances before the spike and remove after. This uses Amazon EC2 Auto Scaling time-based policies to proactively adjust the desired capacity, so instances are fully registered and warmed up when the traffic surge hits. Unlike reactive dynamic scaling, scheduled scaling eliminates the lag that can cause latency or throttling during flash traffic, and then scales back down automatically after the spike to avoid paying for unused resources.
- ✗
Use Spot Instances for the entire workload.
Why it's wrong here
Using Spot Instances for the entire workload is risky because Spot capacity can be reclaimed by AWS at any time with only a two-minute warning, causing abrupt interruptions. A production web application requires high availability and consistent performance; replacing its fleet with Spot Instances would lead to sudden instance terminations, failed requests, and potential data loss. While Spot is cost-effective for fault-tolerant and stateless workloads, it is not suitable for all production traffic without a robust mixed strategy.
- ✗
Use larger instance types to handle the spikes without scaling.
Why it's wrong here
Permanently running larger instance types to absorb spikes forces you to pay for peak capacity around the clock, even though normal traffic may only need a fraction of that compute. This approach also creates a vertical scaling ceiling, meaning once you max out the largest available instance type you cannot grow further, and a single larger instance becomes a bigger failure domain. Horizontal scaling with smaller instances is more granular and can be scheduled to match actual load, reducing waste during off-peak hours.
- ✗
Use On-Demand instances exclusively to handle the spikes.
Why it's wrong here
On-Demand instances give you flexibility and no upfront commitment, but they are priced at the full rate with no volume discounts, making them the most expensive way to handle frequently recurring spikes. Simply running On-Demand instances alone does not automatically adjust capacity; you would still need scaling policies, and you would pay the premium for every instance during every spike. For predictable traffic, a baseline of On-Demand (or Reserved Instances) combined with scheduled additions is far cheaper than scaling up the entire baseline on On-Demand.
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Variation 1. A company is running a web application on a fleet of EC2 instances behind an Application Load Balancer. The application experiences variable traffic patterns with predictable spikes every day at 2 PM. The company wants to optimize costs while maintaining performance. Which solution is MOST cost-effective?
medium- A.Use manual scaling by adjusting the desired capacity each day at 2 PM.
- B.Purchase Reserved Instances for the entire fleet to reduce costs.
- ✓ C.Use scheduled scaling to add instances before the spike and remove them after.
- D.Use dynamic scaling policies based on CPU utilization.
Why C: Scheduled scaling is the correct answer because the traffic spikes are predictable and occur at a known time (2 PM daily). Scheduled scaling allows you to define a schedule (using cron expressions) to automatically increase the desired capacity of the Auto Scaling group before the spike and decrease it afterward, ensuring performance while minimizing costs during off-peak hours. This is more cost-effective than manual scaling because it eliminates the need for human intervention and ensures instances are only running when needed.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This SOA-C02 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the SOA-C02 exam.