What is the relative timeframe used for detecting traffic anomalies?

The correct timeframe for detecting traffic anomalies is 7 days ago. This period is significant because it provides a sufficient amount of historical data to analyze trends and patterns in traffic behavior. Anomalies are often identified by comparing current traffic levels with those from a week prior, allowing Dynatrace to determine if there are deviations from typical performance or usage patterns. By looking back 7 days, the system can effectively assess variations that might indicate underlying issues, peak usage times, or extraordinary events that could impact application performance or user experience.

Shorter timeframes, such as 1 day or 3 days, may not capture enough data variability to confidently identify true anomalies. Conversely, a longer timeframe like 14 days could reflect outdated trends that may no longer be relevant, leading to misinterpretations of traffic patterns. The 7-day benchmark strikes a balance between relevance and the robustness of data for anomaly detection, making it a practical choice for monitoring purposes.