A team configures a Metric Alert with Dynamic Thresholds. What does this provide over static thresholds?
- A Faster alerting
- B ML-based threshold that adapts to metric's historical pattern, reducing false positives from seasonal variation (correct answer)
- C Real-time alerting
- D Multiple threshold sensitivity levels only
Shortcut: Dynamic Thresholds use machine learning to establish expected baselines from historical data. Alerts fire only when the metric deviates beyond the learned pattern, reducing noise from predictable daily/weekly cycles.