SAP-C02 Practice Question: Design Solutions for Organizational Complexity
A company is migrating a legacy monolithic application to a microservices architecture on AWS. The application has strict latency requirements and must be deployed across multiple Availability Zones. Which design strategy BEST meets these requirements while minimizing operational overhead?
⚠ Common exam trap
Watch out — candidates often choose Lambda for its serverless simplicity, but fail to consider the cold start latency and 15-minute execution limit that make it unsuitable for strict latency requirements and long-running microservices.
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
✓
Use Amazon ECS with Fargate launch type, defining services across multiple AZs.
Amazon ECS with Fargate is the best choice because it provides serverless container orchestration, automatically managing infrastructure and scaling. By deploying services across multiple Availability Zones, it ensures high availability and low-latency communication without the operational overhead of managing EC2 instances or Kubernetes control planes. AWS Lambda introduces cold start latency and a 15-minute execution limit, making it unsuitable for strict latency requirements and long-running microservices. EC2 instances and EKS require more operational overhead for patching and scaling. Fargate minimizes that overhead while meeting latency and multi-AZ requirements.
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 Amazon ECS with Fargate launch type, defining services across multiple AZs.
Why this is correct
Fargate manages containers serverlessly, reducing overhead and enabling multi-AZ deployment.
- ✗
Use AWS Lambda functions for each microservice, triggered by API Gateway.
Why it's wrong here
Lambda may not fit long-running or latency-sensitive services.
- ✗
Deploy each microservice on Amazon EC2 instances in an Auto Scaling group across AZs.
Why it's wrong here
EC2 increases operational overhead for patching and scaling.
- ✗
Use Amazon EKS with worker nodes on EC2, and deploy microservices as Kubernetes pods.
Why it's wrong here
EKS adds management overhead for the control plane.
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 by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This SAP-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 SAP-C02 exam.