公开(公告)号：US11487746B2

公开(公告)日：2022-11-01

申请号：US16902497

申请日：2020-06-16

Applicant: Dynatrace LLC

Inventor： Otmar Ertl

IPC: G06F16/23 ,  G06F16/25 ,  G06F11/30 ,  G06F11/34 ,  G06Q10/06 ,  H04L41/12 ,  H04L41/0686 ,  H04L67/75

Abstract: A system and method is disclosed for identifying and evaluating the business relevant impact of observed operating anomalies of monitored components of computing environments like data centers or cloud computing environments. The disclosed technology uses end-to-end transaction trace, availability and resource utilization data in combination with topology data received from agents deployed to the monitored computing environment. An abnormal operating condition is localized within a topological model of the monitored environment and has a defined temporal extent. On detection of an anomaly, affected transaction traces are selected that used the topology entity on which the anomaly was observed while the anomaly existed. Those transactions are then traced backwards, until a topology entity is reached that represents an entry point of monitored system. The affected transactions are compared with unaffected transactions that entered via the entry point to determine the extent to which the entry service is affected by the abnormal behavior.

公开(公告)号：US10817358B2

公开(公告)日：2020-10-27

申请号：US15997734

申请日：2018-06-05

Applicant: Dynatrace LLC

Inventor： Otmar Ertl ,  Ernst Ambichl

IPC: G06F11/00 ,  G06F11/07 ,  G06F11/34 ,  G06F11/30

Abstract: A system and method for the distributed analysis of high frequency transaction trace data to constantly categorize incoming transaction data, identify relevant transaction categories, create per-category statistical reference and current data and perform statistical tests to identify transaction categories showing overall statistically relevant performance anomalies. The relevant transaction category detection considers both the relative transaction frequency of categories compared to the overall transaction frequency and the temporal stability of a transaction category over an observation duration. The statistical data generated for the anomaly tests contains next to data describing the overall performance of transactions of a category also data describing the transaction execution context, like the number of concurrently executed transactions or transaction load during an observation period. Anomaly tests consider current and reference execution context data in addition to statistic performance data to determine if detected statistical performance anomalies should be reported.