AWS Certified Solutions Architect – Associate (SAA-C03)Design Cost-Optimized ArchitecturesMedium
A startup is deploying a new web application on AWS that uses Amazon EC2 instances behind an Application Load Balancer (ALB). The application experiences predictable traffic spikes during business hours and very low traffic overnight. The company wants to ensure high availability and responsiveness during peak times while minimizing costs during off-peak hours. Which EC2 Auto Scaling configuration would be most cost-effective?
- AScheduled Scaling Policy to adjust capacity based on time.
- BStep Scaling Policy based on custom metric (e.g., requests per target).
- CSimple Scaling Policy based on network utilization.
- DTarget Tracking Scaling Policy based on CPU utilization.
Show answer & explanationAnswer & explanation
Correct answer: A. Scheduled Scaling Policy to adjust capacity based on time.
Scheduled Scaling Policies are ideal for predictable traffic patterns, such as business hours and overnight lulls. They allow you to scale out before a spike and scale in before a lull, optimizing costs by only running necessary instances when needed.
Why the other options are wrong
- B. Step Scaling is more for reactive scaling based on thresholds, whereas scheduled scaling proactively addresses known patterns.
- C. Simple Scaling is a legacy policy type, less flexible and responsive than others, and not ideal for predictable patterns.
- D. Target Tracking is good for dynamic, unpredictable loads, but a scheduled policy is more cost-effective for predictable spikes.
EC2 Auto Scaling Scheduled Scaling
An Auto Scaling policy that allows you to scale your EC2 instances up or down based on a predictable schedule. This is useful for applications with known traffic patterns, such as daily or weekly spikes and lulls.
- Proactively adjusts capacity based on time.
- Ideal for predictable traffic patterns.
- Optimizes costs by scaling down during off-peak hours.
Memory trick: Schedule your scales for predictable peaks and valleys.