Example Concept: Implement predictive autoscaling by analyzing historical usage patterns and applying machine learning models to forecast demand. This approach allows you to preemptively scale resources up or down based on predicted load, reducing the need for reactive scaling and minimizing idle resource costs. Additionally, consider using scheduled scaling for predictable workloads, and adjust scaling thresholds to prevent unnecessary scaling actions during transient load spikes.