Which scaling strategy should a solutions architect recommend to meet these requirements?
Implement dynamic scaling with step scaling based on average CPU utilization from the EC2 instances.
Enable predictive scaling to forecast and scale. Configure dynamic scaling with target tracking.
Create an automated scheduled scaling action based on the traffic patterns of the web application.
Set up a simple scaling policy. Increase the cooldown period based on the EC2 instance startup time.
Explanations:
Step scaling based on average CPU utilization may not effectively respond to changing traffic patterns, as it only considers CPU metrics and not the overall workload trends or forecasts. This could lead to suboptimal scaling during peak and off-peak times.
This option combines predictive scaling to analyze historical trends with dynamic scaling using target tracking, allowing the system to automatically adjust based on both forecasted demand and real-time utilization changes. This meets the requirement for a comprehensive scaling strategy.
Scheduled scaling does not adapt to live changes in utilization and relies solely on predefined traffic patterns, which may not accurately reflect actual demand or workload fluctuations. It is not as flexible as combining predictive and dynamic scaling methods.
Simple scaling policies and extended cooldown periods do not account for real-time workload analysis or historical trends. This approach may delay scaling actions unnecessarily and does not leverage the benefits of predictive analytics or dynamic adjustments.
I calculate that the answer is:
Enable predictive scaling to forecast and scale. Configure dynamic scaling with target tracking.