SOA-C02 Question 57
Single answerA company uses an application hosted on Amazon EC2 instances behind an Application Load Balancer (ALB). The SysOps Administrator is tasked with setting up an Auto Scaling plan to handle varying traffic patterns. The application experiences predictable traffic spikes during business hours and significantly lower traffic during nights and weekends. Which Auto Scaling plan should the SysOps Administrator configure to optimize cost while ensuring availability?
- A
Configure a target tracking scaling policy based on CPU utilization.
- B
Set up a scheduled scaling policy to scale up during business hours and scale down during nights and weekends.
- C
Use a step scaling policy to increase or decrease capacity based on specific CloudWatch alarm thresholds.
- D
Implement predictive scaling to automatically forecast traffic and adjust capacity accordingly.
Show answer and explanation
Correct answer: B
Explanation
Scheduled scaling is the best choice for predictable traffic patterns, such as regular spikes during business hours and lower traffic at other times. It allows the administrator to predefine scaling actions to optimize costs without compromising availability. Other scaling methods, like target tracking, step scaling, or predictive scaling, are better suited for dynamic or less predictable workloads.
- A. Incorrect.
Target tracking scaling policies are typically used for dynamic workloads where scaling is based on maintaining a specific metric, such as CPU utilization. However, this scenario involves predictable traffic patterns, which makes scheduled scaling more suitable.
- B. Correct.
Scheduled scaling allows the administrator to specify scaling actions to occur at predetermined times, which is ideal for predictable traffic patterns like the ones described in this scenario. It ensures cost optimization by scaling resources only when needed.
- C. Incorrect.
Step scaling is effective for responding to unpredictable changes in traffic by adjusting capacity based on CloudWatch alarms. However, it is not ideal for scenarios with predictable traffic patterns.
- D. Incorrect.
Predictive scaling is useful for applications with highly dynamic traffic patterns where advanced machine learning models can forecast changes. However, for predictable patterns like business hours, scheduled scaling is simpler and more effective.