公开(公告)号：US20180276142A1

公开(公告)日：2018-09-27

申请号：US15467039

申请日：2017-03-23

Applicant: Hewlett Packard Enterprise Development LP

Inventor： Joseph E. Algieri ,  John J. Sengenberger ,  Siamak Nazari

IPC: G06F12/128 ,  G06F3/06 ,  G06F12/0808

CPC classification number: G06F12/128 ,  G06F3/0619 ,  G06F3/0656 ,  G06F3/0689 ,  G06F12/0808 ,  G06F2212/1041 ,  G06F2212/621

Abstract: Examples discussed herein include receiving a notification about an event occurring in a storage array. In response to receiving the notification a cache of the storage array may be frozen and the data in the cache may be flushed to a persistent storage. The data in the cache is stored in the cache prior to the event. Examples also include receiving first data in a first host write request that is received after the event from a host device, sending a write request complete signal to the host device, and flushing the first data to the persistent storage. The first data is flushed after the data in cache is flushed.

公开(公告)号：US11070455B2

公开(公告)日：2021-07-20

申请号：US16034567

申请日：2018-07-13

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： Mayukh Dutta ,  Manoj Srivatsav ,  John J. Sengenberger

IPC: G06F11/34 ,  H04L29/08 ,  G06F11/30 ,  H04L12/26 ,  G06K9/62

Abstract: A system or method for identifying anomalies indicating misconfiguration or software bugs in a data storage network that may include capturing data storage network latency metrics, identifying periods of high latency in the captured latency metrics, applying a statistical deviation operation to the latency metrics in the periods of identified high latency, and identifying outliers in the statistically deviated latency metrics. The method further includes calculating a median of the identified outliers, normalizing the median of the identified outliers, and scoring the normalized median values of the identified outliers.

公开(公告)号：US20190334802A1

公开(公告)日：2019-10-31

申请号：US16034567

申请日：2018-07-13

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： Mayukh Dutta ,  Manoj Srivatsav ,  John J. Sengenberger

IPC: H04L12/26 ,  G06F11/34 ,  G06F11/30 ,  H04L29/08 ,  G06K9/62

Abstract: A system or method for identifying anomalies indicating misconfiguration or software bugs in a data storage network that may include capturing data storage network latency metrics, identifying periods of high latency in the captured latency metrics, applying a statistical deviation operation to the latency metrics in the periods of identified high latency, and identifying outliers in the statistically deviated latency metrics. The method further includes calculating a median of the identified outliers, normalizing the median of the identified outliers, and scoring the normalized median values of the identified outliers.

公开(公告)号：US20190334801A1

公开(公告)日：2019-10-31

申请号：US16034531

申请日：2018-07-13

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： Mayukh Dutta ,  Manoj Srivatsav ,  John J. Sengenberger

IPC: H04L12/26 ,  G06F11/34 ,  G06F11/30 ,  H04L29/08 ,  G06K9/62

Abstract: A system or method for identifying latency contributors in a data storage network, that may include creating a historical workload fingerprint model for a data storage network from training data, along with monitoring and classifying a current sample data from the data storage network into a cluster, current workload fingerprint, and current workload type. The method may further include assigning a score to the current sample data based on the historical workload fingerprint model and correlating measured latency values from the current sample data to historically measured latency related factors to create a latency score chart that identifies factors causing latency in the data storage network for the current sample data.

公开(公告)号：US10778552B2

公开(公告)日：2020-09-15

申请号：US16034531

申请日：2018-07-13

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： Mayukh Dutta ,  Manoj Srivatsav ,  John J. Sengenberger

IPC: G06F15/16 ,  H04L12/26 ,  G06F11/34 ,  G06K9/62 ,  H04L29/08 ,  G06F11/30

Abstract: A system or method for identifying latency contributors in a data storage network, that may include creating a historical workload fingerprint model for a data storage network from training data, along with monitoring and classifying a current sample data from the data storage network into a cluster, current workload fingerprint, and current workload type. The method may further include assigning a score to the current sample data based on the historical workload fingerprint model and correlating measured latency values from the current sample data to historically measured latency related factors to create a latency score chart that identifies factors causing latency in the data storage network for the current sample data.

公开(公告)号：US20190334786A1

公开(公告)日：2019-10-31

申请号：US16034608

申请日：2018-07-13

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： Mayukh Dutta ,  Manoj Srivatsav ,  John J. Sengenberger

IPC: H04L12/24 ,  H04L12/26 ,  G06F11/34 ,  G06F11/30 ,  H04L29/08 ,  G06K9/62

Abstract: A system or method for predicting workload and latency patterns in a data storage network that includes training a model in a cloud based on data storage network I/O data, monitoring sample I/O data in a data storage network at predetermined intervals, and determining a workload fingerprint in the trained model that corresponds to the sample I/O data. The method further includes calculating a workload value for the sample I/O data and forecasting future workload and latency patterns using an autoregressive integrated moving average statistical calculation based on the sample I/O time series data and the calculated workload value for the sample I/O.