Anomaly detection is an algorithmic feature that allows you to identify when a metric is behaving differently than it has in the past, taking into account seasonal day-of-week and time-of-day patterns. It's well-suited for metrics with recurring patterns that are hard or impossible to monitor with threshold-based alerting. For example, anomaly detection can help you discover when your web traffic is unusually low on a weekday afternoon—even though that same level of traffic would be perfectly normal later in the evening.