公开(公告)号：US20210141900A1

公开(公告)日：2021-05-13

申请号：US16682549

申请日：2019-11-13

Applicant: VMware, Inc.

Inventor： Darren Brown ,  Paul Pedersen ,  Keshav Mathur ,  Junyuan Lin ,  Nicholas Kushmerick ,  Jinyi Lu ,  Xing Wang ,  Peng Gao

IPC: G06F21/56

Abstract: Computational methods and systems for detecting and troubleshooting anomalous behavior in distributed applications executing in a distributed computing system are described herein. Methods and systems discover nodes comprising the application. Anomaly detection monitors the metrics associated with the nodes for anomalous behavior in order to identify an approximate point in time when anomalous behavior begins to adversely impact performance of the application. Anomaly detection also monitors logs messages associated with the nodes to detect anomalous behavior recorded in the log messages. When anomalous behavior is detected in either the metrics and/or the log messages an alert identifying the anomalous behavior is generated. Troubleshooting guides an administrator and/or application owner to investigate the root cause of the anomalous behavior. Appropriate remedial measures may be determined based on the root cause and automatically or manually executed to correct the problem.

公开(公告)号：US10776166B2

公开(公告)日：2020-09-15

申请号：US15951523

申请日：2018-04-12

Applicant: VMware, Inc.

Inventor： Darren Brown ,  Junyuan Lin ,  Paul Pedersen ,  Keshav Mathur ,  Leah Nutman ,  Peng Gao ,  Xing Wang

IPC: G06F9/46 ,  G06F9/50 ,  G06N7/00

Abstract: Computational methods and systems that proactively manage usage of computational resources of a distributed computing system are described. A sequence of metric data representing usage of a resource is detrended to obtain a sequence of non-trendy metric data. Stochastic process models, a pulse wave model and a seasonal model of the sequence of non-trendy metric data are computed. When a forecast request is received, a sequence of forecasted metric data is computed over a forecast interval based on the estimated trend and one of the pulse wave or seasonal model that matches the periodicity of the sequence of non-trendy metric data. Alternatively, the sequence of forecasted metric data is computed based on the estimated trend and the stochastic process model with a smallest accumulated residual error. Usage of the resource by virtual objects of the distributed computing system may be adjusted based on the sequence of forecasted metric data.

公开(公告)号：US20190317817A1

公开(公告)日：2019-10-17

申请号：US15951523

申请日：2018-04-12

Applicant: VMware, Inc.

Inventor： Darren Brown ,  Junyuan Lin ,  Paul Pedersen ,  Keshav Mathur ,  Leah Nutman ,  Peng Gao ,  Xing Wang

IPC: G06F9/50 ,  G06N7/00

Abstract: Computational methods and systems that proactively manage usage of computational resources of a distributed computing system are described. A sequence of metric data representing usage of a resource is detrended to obtain a sequence of non-trendy metric data. Stochastic process models, a pulse wave model and a seasonal model of the sequence of non-trendy metric data are computed. When a forecast request is received, a sequence of forecasted metric data is computed over a forecast interval based on the estimated trend and one of the pulse wave or seasonal model that matches the periodicity of the sequence of non-trendy metric data. Alternatively, the sequence of forecasted metric data is computed based on the estimated trend and the stochastic process model with a smallest accumulated residual error. Usage of the resource by virtual objects of the distributed computing system may be adjusted based on the sequence of forecasted metric data.