SOA-C02 Question 53
Single answerYour company runs a high-traffic e-commerce website hosted on an Auto Scaling group of Amazon EC2 instances behind an Application Load Balancer (ALB). During seasonal sales events, traffic spikes significantly, causing latency issues for users. The website is designed to handle these spikes, but you notice a delay in scaling out additional instances. What is the BEST approach to improve the system's scalability and elasticity to handle these traffic surges effectively?
- A
Reduce the cooldown period for the Auto Scaling group.
- B
Configure a scheduled scaling policy to add instances before the sales events begin.
- C
Enable Elastic Load Balancing (ELB) access logs to analyze traffic patterns.
- D
Switch the Auto Scaling group to a fixed-size scaling configuration.
Show answer and explanation
Correct answer: B
Explanation
Scheduled scaling is the best solution for scenarios with predictable traffic spikes, such as seasonal sales events. By pre-scaling resources, you can ensure that the system is prepared to handle the increased load without latency or delays in scaling. Other options either do not address the root cause or remove the benefits of dynamic scalability and elasticity.
- A. Incorrect.
Reducing the cooldown period may result in unnecessary or rapid scaling actions, potentially leading to instability or over-provisioning of resources without solving the issue of scaling proactively for planned traffic spikes.
- B. Correct.
Configuring a scheduled scaling policy ensures that additional instances are pre-warmed and ready to handle the anticipated traffic spike during seasonal sales events. This preemptive scaling approach is effective for predictable traffic patterns.
- C. Incorrect.
Enabling ELB access logs is useful for analyzing traffic patterns, but it does not directly improve the scalability or elasticity of the system during traffic surges.
- D. Incorrect.
Switching to a fixed-size scaling configuration eliminates the benefits of Auto Scaling, making the system incapable of dynamically adjusting to changing traffic demands.