Which factor does Dynatrace use primarily for detecting user action performance degradation?

Dynatrace primarily relies on automated baselining of median and percentile performance to detect user action performance degradation. This approach utilizes advanced algorithms to establish performance baselines that dynamically adapt to varying conditions. By continuously monitoring user actions, Dynatrace can identify deviations from these established baselines—specifically when performance falls below the median or specified percentiles. This allows it to flag performance issues effectively, enabling organizations to respond proactively rather than reactively.

While customer feedback can provide insights into user experience, it is subjective and often lacks the immediacy of performance data. Load balancing statistics are useful for understanding the distribution of traffic across servers but do not directly measure user action performance. Direct application monitoring captures performance metrics but does not revolve around the comparative analysis against historical data, which is crucial for identifying degradation trends over time. Hence, automated baselining stands out as the key factor enabling dynamic detection of performance drops in user interactions.