公开(公告)号：US20200027014A1

公开(公告)日：2020-01-23

申请号：US15394654

申请日：2016-12-29

Applicant: Nutanix, Inc.

Inventor： Jianjun WEN ,  Abhinay NAGPAL ,  Himanshu SHUKLA ,  Binny Sher GILL ,  Cong LIU ,  Shuo YANG

IPC: G06N7/00 ,  G06N5/02

Abstract: A method for time series analysis of time-oriented usage data pertaining to computing resources of a computing system. A method embodiment commences upon collecting time series datasets, individual ones of the time series datasets comprising time-oriented usage data of a respective individual computing resource. A plurality of prediction models are trained using portions of time-oriented data. The trained models are evaluated to determine quantitative measures pertaining to predictive accuracy. One of the trained models is selected and then applied over another time series dataset of the individual resource to generate a plurality of individual resource usage predictions. The individual resource usage predictions are used to calculate seasonally-adjusted resource usage demand amounts over a future time period. The resource usage demand amounts are compared to availability of the resource to form a runway that refers to a future time period when the resource is predicted to be demanded to its capacity.

公开(公告)号：US20200034745A1

公开(公告)日：2020-01-30

申请号：US15251244

申请日：2016-08-30

Applicant: Nutanix, Inc.

Inventor： Abhinay NAGPAL ,  Himanshu SHUKLA ,  Cong LIU ,  Jianjun WEN

IPC: G06N99/00 ,  G06N5/02

Abstract: A system for implementing seasonal time series analysis and forecasting using a distributed tournament selection process. Time series analysis is initiated by a prediction or runway event trigger. Prediction events include a determination of the availability of one or more resources at a given point in time or over a given time period. A runway event may include a determination of when a resource is below a minimum threshold level of availability. Training of the prediction models is based data taken from different time periods, accounting for any combination of time periods and/or for differing sampling frequencies or ranges. Processes for prosecuting a tournament to identify winning models are parallelized to achieve low latency tournament results. Ranking of each model and/or some combination of models is based on how precisely and/or conclusively the models match a determined set of training data.

公开(公告)号：US20190340094A1

公开(公告)日：2019-11-07

申请号：US16051296

申请日：2018-07-31

Applicant: Nutanix, Inc.

Inventor： Zihong LU ,  Abhinay NAGPAL ,  Harry Hai Yang ,  Himanshu SHUKLA ,  Shyama Sundar DURISETI ,  Surendran MADHESWARAN ,  Cong LIU

IPC: G06F11/30 ,  H04L12/26 ,  H04L12/24 ,  H04L29/06

Abstract: Systems for alerting in computing systems. A method commences by defining a plurality of analysis zones bounded by respective ranges of system metric values, which ranges in turn correspond a plurality of system behavior classifications. System observations are taken while the computing system is running. A system observation comprising a measured metric value is classified into one or more of the behavior classifications. Based on the classification, one or more alert analysis processes are invoked to analyze the system observation and make a remediation recommendation. An alert or remediation is raised or suppressed based on one or more zone-based analysis outcomes. An alert is raised when anomalous behavior is detected. The system makes ongoing observations to learn how and when to classify a measured metric value into normal or anomalous behaviors. As changes occur in the system configuration, the analysis zones are adjusted to reflect changing bounds of the zones.