公开(公告)号：US09542103B2

公开(公告)日：2017-01-10

申请号：US14535587

申请日：2014-11-07

Applicant: NETAPP, INC.

Inventor： Kevin Faulkner ,  Leon Fairbanks ,  Siu Wu ,  Vinod Vasant Pai ,  Ulhas Pai

IPC: G06F3/06 ,  G06F11/30 ,  G06F11/34

CPC classification number: G06F3/0613 ,  G06F3/0653 ,  G06F3/067 ,  G06F3/0689 ,  G06F11/3034 ,  G06F11/3419 ,  G06F11/3452 ,  G06F11/3485

Abstract: Methods and systems for monitoring quality of service (QOS) data for a plurality of storage volumes are provided. QOS data is collected for the plurality of storage volumes and includes a response time in which each of the plurality of storage volumes respond to an input/output (I/O) request. The process determines an average of N collected QOS data points at any given time; and iteratively analyzes each QOS data point to detect if a step-up or a step-down function has occurred, where a step-up function represents an unpredictable increase in value of a data point and a step-down function is an unpredictable decrease in value of the data point. A subset of the N QOS data points based on when the step-up function or step-down function occurs is selected for analysis and an expected range for future QOS data based on the subset of the N QOS data points is generated.

Abstract translation: 提供了用于监视多个存储卷的服务质量（QOS）数据的方法和系统。 针对多个存储卷收集QOS数据，并且包括其中多个存储卷中的每一个对输入/输出（I / O）请求做出响应的响应时间。 该过程确定在任何给定时间N个收集的QOS数据点的平均值; 并且迭代地分析每个QOS数据点以检测是否发生升压或降压功能，其中升压功能表示数据点的值的不可预测的增加，并且降压功能是不可预测的降低 数据点的值。 选择基于升压功能或降压功能何时发生的NQOS数据点的子集用于分析，并且生成基于N个QOS数据点的子集的未来QOS数据的期望范围。

公开(公告)号：US09542115B1

公开(公告)日：2017-01-10

申请号：US14747313

申请日：2015-06-23

Applicant: NETAPP, INC.

Inventor： Curtis Hrischuk ,  David Gilbert Roberts ,  Ulhas Pai ,  Kushagra Mittal ,  Peter Adam Smith ,  Purushottam Jha

IPC: G06F12/00 ,  G06F3/06 ,  H04L29/08 ,  H04L12/26

CPC classification number: G06F3/0631 ,  G06F3/0604 ,  G06F3/067 ,  H04L41/0631 ,  H04L43/045 ,  H04L43/0852 ,  H04L43/16 ,  H04L67/1097

Abstract: Methods and systems for managing resources in a storage system are provided. The methods include tracking performance of a plurality of resources used for reading and writing information at storage devices in a networked storage system, each resource represented by a logical object in a hierarchical structure and performance data associated with each logical object is maintained by a processor executing a management application out of a memory device; identifying a root object associated with a resource having a performance issue as indicated by a threshold violation for the resource; selecting a related object associated with a resource similar to the resource of the root object by the management application for comparing performance data of the root object with the related object; and using the comparison to verify that the root object is a root cause of the performance issue.

Abstract translation: 提供了用于管理存储系统中的资源的方法和系统。 所述方法包括跟踪用于在网络存储系统中的存储设备处读取和写入信息的多个资源的性能，由分层结构中的逻辑对象表示的每个资源和与每个逻辑对象相关联的性能数据由处理器执行 存储设备中的管理应用; 识别与资源的阈值冲突所指示的具有性能问题的资源相关联的根对象; 通过所述管理应用程序选择与所述根对象的资源类似的资源相关联的相关对象，用于将所述根对象的性能数据与相关对象进行比较; 并使用比较来验证根对象是性能问题的根本原因。

公开(公告)号：US20160378389A1

公开(公告)日：2016-12-29

申请号：US14747313

申请日：2015-06-23

Applicant: NETAPP, INC.

Inventor： Curtis Hrischuk ,  David Gilbert Roberts ,  Ulhas Pai ,  Kushagra Mittal ,  Peter Adam Smith ,  Purushottam Jha

IPC: G06F3/06 ,  H04L12/26 ,  H04L29/08

CPC classification number: G06F3/0631 ,  G06F3/0604 ,  G06F3/067 ,  H04L41/0631 ,  H04L43/045 ,  H04L43/0852 ,  H04L43/16 ,  H04L67/1097

Abstract: Methods and systems for managing resources in a storage system are provided. The methods include tracking performance of a plurality of resources used for reading and writing information at storage devices in a networked storage system, each resource represented by a logical object in a hierarchical structure and performance data associated with each logical object is maintained by a processor executing a management application out of a memory device; identifying a root object associated with a resource having a performance issue as indicated by a threshold violation for the resource; selecting a related object associated with a resource similar to the resource of the root object by the management application for comparing performance data of the root object with the related object; and using the comparison to verify that the root object is a root cause of the performance issue.

Abstract translation: 提供了用于管理存储系统中的资源的方法和系统。 所述方法包括跟踪用于在网络存储系统中的存储设备处读取和写入信息的多个资源的性能，由分层结构中的逻辑对象表示的每个资源和与每个逻辑对象相关联的性能数据由处理器执行 存储设备中的管理应用; 识别与资源的阈值冲突所指示的具有性能问题的资源相关联的根对象; 通过所述管理应用程序选择与所述根对象的资源类似的资源相关联的相关对象，用于将所述根对象的性能数据与相关对象进行比较; 并使用比较来验证根对象是性能问题的根本原因。

公开(公告)号：US20150199139A1

公开(公告)日：2015-07-16

申请号：US14535587

申请日：2014-11-07

Applicant: NETAPP, INC.

Inventor： Kevin Faulkner ,  Leon Fairbanks ,  Siu Wu ,  Vinod Vasant Pai ,  Ulhas Pai

IPC: G06F3/06 ,  G06F11/34

CPC classification number: G06F3/0613 ,  G06F3/0653 ,  G06F3/067 ,  G06F3/0689 ,  G06F11/3034 ,  G06F11/3419 ,  G06F11/3452 ,  G06F11/3485

Abstract: Methods and systems for monitoring quality of service (QOS) data for a plurality of storage volumes are provided. QOS data is collected for the plurality of storage volumes and includes a response time in which each of the plurality of storage volumes respond to an input/output (I/O) request. The process determines an average of N collected QOS data points at any given time; and iteratively analyzes each QOS data point to detect if a step-up or a step-down function has occurred, where a step-up function represents an unpredictable increase in value of a data point and a step-down function is an unpredictable decrease in value of the data point. A subset of the N QOS data points based on when the step-up function or step-down function occurs is selected for analysis and an expected range for future QOS data based on the subset of the N QOS data points is generated.

Abstract translation: 提供了用于监视多个存储卷的服务质量（QOS）数据的方法和系统。 针对多个存储卷收集QOS数据，并且包括其中多个存储卷中的每一个对输入/输出（I / O）请求做出响应的响应时间。 该过程确定在任何给定时间N个收集的QOS数据点的平均值; 并且迭代地分析每个QOS数据点以检测是否发生升压或降压功能，其中升压功能表示数据点的值的不可预测的增加，并且降压功能是不可预测的降低 数据点的值。 选择基于升压功能或降压功能何时发生的NQOS数据点的子集用于分析，并且生成基于N个QOS数据点的子集的未来QOS数据的期望范围。