Which type of autoscaling automatically adjusts based on specified metrics?

Metrics-based autoscaling is the correct answer because it specifically refers to the automatic adjustment of computing resources based on real-time data and performance metrics. This approach uses predefined thresholds for various indicators such as CPU usage, memory consumption, and application latency. When these metrics exceed or fall below the specified limits, the autoscaling mechanism automatically scales resources up or down accordingly.

This type of autoscaling is particularly effective in environments where workload fluctuations can be predicted based on actual usage patterns, ensuring optimal resource utilization and cost efficiency. By focusing on real-time metrics, this method allows for responsive and intelligent scaling that aligns closely with current system demands.

In comparison, time-based autoscaling relies on schedules rather than real-time metrics, while traffic-based autoscaling primarily focuses on incoming requests or traffic volume, which may not capture the entire performance spectrum. Dynamic autoscaling is a broader term that often encompasses metrics-based approaches but may not specifically emphasize the direct relationship to detailed performance indicators as effectively as metrics-based autoscaling does.