Answer: Configure a scheduled scaling policy for the Auto Scaling group to launch new instances before peak hours.

## Explanation The correct answer is **D** because: 1. **Predictable Peak Hours**: The problem states that application peak hours occur at the same time each day, which is a predictable pattern. 2. **Performance Issue Timing**: Users report slow performance at the **start** of peak hours, but the application performs normally 2-3 hours after peak hours begin. This indicates that the Auto Scaling group eventually scales up based on metrics (likely CPU utilization), but this reactive scaling happens too slowly. 3. **Scheduled Scaling vs. Dynamic Scaling**: - **Dynamic scaling** (options B and C) reacts to metrics like CPU or memory utilization. This is reactive and takes time to trigger and complete (instance launch time + application warm-up time). - **Scheduled scaling** (option D) proactively scales capacity before the predictable peak hours begin, ensuring sufficient capacity is available when needed. 4. **Why not the other options**: - **A**: An Application Load Balancer helps distribute traffic but doesn't address the capacity issue - it would just distribute traffic to insufficient instances. - **B & C**: Dynamic scaling based on memory or CPU utilization would still cause the initial performance degradation because scaling would only trigger AFTER metrics exceed thresholds, and there's a delay for instances to launch and become ready. 5. **Best Practice**: For predictable traffic patterns, AWS recommends using scheduled scaling actions to ensure capacity is available before the load increases, rather than waiting for metrics to trigger scaling. **Key AWS Concepts**: - **Scheduled Scaling**: Best for predictable, recurring patterns - **Dynamic Scaling**: Best for unpredictable, variable patterns - **Instance Launch Time**: EC2 instances take time to launch (minutes) and applications may need additional warm-up time

Author: LeetQuiz Editorial Team