SAA-C03 Design Cost-Optimized Architectures Practice Question
A company runs a containerized order-processing service on Amazon ECS with the Fargate launch type. The service scales out during business hours and scales down to a small baseline overnight. Usage is expected to remain stable for the next two years, and the team wants to reduce Fargate cost without managing any servers. Which action should the solutions architect take?
⚠ Common exam trap
The trap here is assuming that a Fargate workload cannot benefit from any savings plan, when Compute Savings Plans cover Fargate as well as Lambda and EC2.
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
✓
Purchase a Compute Savings Plan that covers the steady Fargate baseline usage
Compute Savings Plans explicitly cover Fargate vCPU and memory usage, so they reduce cost for a serverless container workload without requiring any infrastructure management. Sizing the commitment to the guaranteed overnight baseline discounts the portion of usage that will certainly occur, while the elastic daytime capacity continues to bill at On-Demand rates without over-committing the company.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Enable Fargate Spot for the entire service and remove the On-Demand baseline
Why it's wrong here
Fargate Spot is inexpensive but tasks can be interrupted with a short notice, which is unsuitable for an order-processing service that must reliably accept and complete transactions. It can complement a stable baseline for interruption-tolerant work, but replacing the baseline entirely would risk failed or delayed orders during reclamation events.
- ✓
Purchase a Compute Savings Plan that covers the steady Fargate baseline usage
Why this is correct
Compute Savings Plans apply to Fargate vCPU and memory usage as well as to Lambda and EC2, so they discount the steady portion of this service without requiring any server management. Committing to the overnight baseline captures the discount on usage that is certain to occur, while the variable daytime scale-out remains on On-Demand rates.
- ✗
Purchase a 1-year EC2 Instance Savings Plan sized to the nightly baseline
Why it's wrong here
EC2 Instance Savings Plans apply only to EC2 instance usage, not to Fargate tasks. Because the workload runs exclusively on the Fargate launch type, this commitment would not discount any of the actual consumption, leaving the bill unchanged while adding a commitment that must still be paid.
- ✗
Migrate the service to the EC2 launch type and purchase Reserved Instances for the baseline
Why it's wrong here
Moving to the EC2 launch type would allow reservations, but it also requires the team to manage cluster capacity, patching, and scaling of instances, which contradicts the stated goal of not managing servers. It trades a pricing problem for an operational burden the team explicitly wants to avoid.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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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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