Hi @SrikanthSamraj,
Auto-adaptive threholds in Dynatrace provide a dynamic approach to anomoly detection by allowing reference values to change over time. This method offers significant advantages over statick thresholds, which require manual ajustments and predefined values.
Auto-adaptive thresholds automatically adjust to the normal behavior of each metric, eliminating the need for manual recalibration. When configuring anomaly detection for multiple entities, such as hosts, each entity gets its own adaptive threshold, ensuring more accurate and independant evaluations. This flexbility helps in avoiding false positives that often occur with static thresholds in environments with fluctuating metrics.
A practical example can be seen with disk write times. A static threshold might be set based on initial data, but as disk usage changes, this threshold could lead to false alerts. Auto-adaptive thresholds, however, adjust to these changes in real-time, providing more reliable anomaly detection without constant manual intervention.
