How does automated baselining work in Dynatrace?

Automated baselining in Dynatrace operates by generating a baseline cube based on actual application traffic. This method leverages historical data to dynamically create a baseline of normal performance metrics, which reflects typical user behavior and system performance over time. By analyzing the variations in these metrics, Dynatrace can identify anomalies and deviations from established patterns, allowing for proactive performance monitoring and alerting.

This approach is advantageous as it minimizes reliance on manual inputs or user interventions, making it scalable and efficient for environments that experience fluctuating traffic patterns. As application environments change, the automated baselining process continuously adapts to new data, ensuring that the baseline remains relevant and accurately reflects performance norms.

The other methods mentioned, such as manual inputs or restricting data collection to single sessions, do not provide the dynamic and comprehensive assessment needed for effective monitoring. Automated baselining eliminates the need for user intervention, allowing for a more streamlined and accurate analysis of application performance over time.