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SOA-C02 Cost and Performance Optimization Practice Question

A company runs a web application on EC2 instances behind an Application Load Balancer (ALB). The application experiences variable traffic with occasional spikes. The SysOps administrator wants to optimize costs while ensuring that the application can handle spikes without performance degradation. The current setup uses a fixed number of instances. Which action should the administrator take?

⚠ Common exam trap

SOA-C02 often tests the misconception that Reserved Instances or larger instance types solve variable traffic — the exam expects recognition that elasticity (Auto Scaling) is required for spikes, while RIs only address steady-state cost.

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

✓

Implement an Auto Scaling group with a target tracking scaling policy based on ALB request count per target.

An Auto Scaling group with a target tracking policy based on ALB request count per target automatically scales instances in and out to match traffic, handling spikes while minimizing cost during low-traffic periods. This directly addresses variable traffic with occasional 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.

  • ✗

    Purchase Reserved Instances for the current number of instances to reduce hourly cost.

    Why it's wrong here

    Dedicated Reserved Instances provide a discounted hourly rate in exchange for a 1-year or 3-year commitment, but they must be purchased for a fixed quantity of instances. For a workload with variable traffic, this locks you into paying for a certain number of instances regardless of actual demand; during low periods you waste money on idle capacity, and during spikes you still need additional On-Demand instances. Thus, while they reduce baseline cost, they do not address the core requirement of elasticity.

  • ✓

    Implement an Auto Scaling group with a target tracking scaling policy based on ALB request count per target.

    Why this is correct

    An Auto Scaling group with a target tracking scaling policy based on ALB request count per target continuously monitors the average number of requests each healthy instance receives. When the metric exceeds the target, the policy automatically launches additional EC2 instances, and when it falls below, it terminates instances, ensuring the fleet size tracks actual demand. This dynamic, horizontal scaling optimizes both cost and performance without manual intervention, making it the correct solution for a variable web workload.

  • ✗

    Replace on-demand instances with Spot Instances for all traffic.

    Why it's wrong here

    Spot Instances offer substantial cost savings but can be reclaimed by EC2 with a two-minute warning when capacity is needed elsewhere, causing abrupt loss of instances. Relying on Spot for all traffic means a sudden spike in user demand could coincide with spot reclamation, leading to dropped requests and downtime for the web application. Spot should be reserved for fault-tolerant, stateless workloads, not as the sole capacity for a production site behind an ALB.

  • ✗

    Increase the instance size to a compute-optimized type to handle spikes.

    Why it's wrong here

    Increasing the instance size to a compute-optimized type is a form of vertical scaling that raises the per-hour cost for every hour of operation, including during low-traffic periods when the extra resources are unused. It also creates a fixed capacity ceiling: if a single large instance cannot handle an extreme traffic spike, the application still fails, and there is no room to grow beyond that instance. Auto Scaling, by contrast, allows the number of instances to grow horizontally without bound, matching capacity to demand.

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JA

Written and reviewed by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint

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