Method and system for monitoring and analyzing quality of service in a storage system

Patent metadata

Field	Value
Publication number	US-9542103-B2
Application number	US-201414535587-A
Country	US
Kind code	B2
Filing date	Nov 7, 2014
Priority date	Jan 14, 2014
Publication date	Jan 10, 2017
Grant date	Jan 10, 2017

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.

First claim

What is claimed is:

1. A machine implemented method, comprising:
collecting quality of service (QOS) data for a plurality of storage volumes from a storage operating system of a storage system having a plurality of resources; wherein the QOS data includes a response time in which each of the plurality of storage volumes respond to an input/output (I/O) request; a wait time for each I/O request at each of the resources of the storage system; and a number of visits for each I/O request at each of the resources of the storage system;
determining an average of N collected QOS data points at any given time;
iteratively analyzing 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;
selecting a subset of the N QOS data points based on when the step-up function or step-down function occurs;
generating an expected range for future QOS data based on the subset of the N QOS data points, where the expected range is a range of measured performance activity of a workload over a period of time for predicting future QOS data behavior of the storage volumes; and
monitoring QOS data for each storage volume for determining whether a current QOS data for each storage volume is within the expected range.

2. The method of claim 1 , wherein the expected range provides a dynamic threshold value to a processor executable performance manager for predicting an incident associated with any of the plurality of storage volumes.

3. The method of claim 1 , wherein the expected range provides a dynamic threshold value to a processor executable performance manager for determining if any of the resource is in contention between any of the plurality of storage volumes resulting in a storage volume becoming a victim due to overuse by a bully storage volume.

4. The method of claim 1 , wherein the resources at the storage system are categorized as a service center that services a request and QOS data for the service center includes a number of visits, wait time per visit and service time and a delay center that only moves the request to a next destination whose QOS data includes the number of visits and the wait time per visit.

5. The method of claim 4 , wherein the resources include a processor for a network module that interfaces with clients and operates as a service center and a processor for a storage module that operates as a service center and manages storage devices where information is stored.

6. A non-transitory machine readable storage medium having stored thereon instructions for performing a method, comprising machine executable code which when executed by at least one machine, causes the machine to:
collect quality of service (QOS) data for a plurality of storage volumes from a storage operating system of a storage system having a plurality of resources; wherein the QOS data includes a response time in which each of the plurality of storage volumes respond to an input/output (I/O) request; a wait time for each I/O request at each of the resources of the storage system; and a number of visits for each I/O request at each of the resources of the storage system;
determine an average of N collected QOS data points at any given time;
iteratively analyze 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;
select a subset of the N QOS data points based on when the step-up function or step-down function occurs;
generate an expected range for future QOS data based on the subset of the N QOS data points, where the expected range is a range of measured performance activity of a workload over a period of time for predicting future QOS data behavior of the storage volumes; and
monitor QOS data for each storage volume for determining whether a current QOS data for each storage volume is within the expected range.

7. The storage medium of claim 6 , wherein the expected range provides a dynamic threshold value to a processor executable performance manager for predicting an incident associated with any of the plurality of storage volumes.

8. The storage medium of claim 6 , wherein the expected range provides a dynamic threshold value to a processor executable performance manager for determining if any of the resource is in contention between any of the plurality of storage volumes resulting in a storage volume becoming a victim due to overuse by a bully storage volume.

9. The storage medium of claim 6 , wherein the resources at the storage system are categorized as a service center that services a request and QOS data for the service center includes a number of visits, wait time per visit and service time and a delay center that only moves the request to a next destination whose QOS data includes the number of visits and the wait time per visit.

10. The storage medium of claim 9 , wherein the resources include a processor for a network module that interfaces with clients and operates as a service center and a processor for a storage module that operates as a service center and manages storage devices where information is stored.

11. A system, comprising:
a memory containing machine readable medium comprising machine executable code having stored thereon instructions; and a processor module coupled to the memory, the processor module configured to execute the machine executable code to:
collect quality of service (QOS) data for a plurality of storage volumes from a storage operating system of a storage system having a plurality of resources; wherein the QOS data includes a response time in which each of the plurality of storage volumes respond to an input/output (I/O) request; a wait time for each I/O request at each of the resources of the storage system; and a number of visits for each I/O request at each of the resources of the storage system;
determine an average of N collected QOS data points at any given time;
iteratively analyze 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;
select a subset of the N QOS data points based on when the step-up function or step-down function occurs;
generate an expected range for future QOS data based on the subset of the N QOS data points, where the expected range is a range of measured performance activity of a workload over a period of time for predicting future QOS data behavior of the storage volumes; and
monitor QOS data for each storage volume for determining whether a current QOS data for each storage volume is within the expected range.

12. The system of claim 11 , wherein the expected range provides a dynamic threshold value to a processor executable performance manager for predicting an incident associated with any of the plurality of storage volumes.

13. The system of claim 11 , wherein the expected range provides a dynamic threshold value to a processor executable performance manager for determining if any of the resource is in contention between any of the plurality of storage volumes resulting in a storage volume becoming a victim due to overuse by a bully storage volume.

14. The system of claim 11 , wherein the resources at the storage system are categorized as a service center that services a request and QOS data for the service ce

Assignees

• Netapp Inc

Inventors

• Faulkner Kevin
• Fairbanks Leon
• Wu Siu
• Pai Vinod Vasant
• Pai Ulhas

Classifications

• G06F3/0613 Primary

  in relation to throughput · CPC title

• G06F3/0689

  Disk arrays, e.g. RAID, JBOD · CPC title

• G06F3/0653

  Monitoring storage devices or systems · CPC title

• G06F11/3452

  Performance evaluation by statistical analysis · CPC title

• G06F3/067

  Distributed or networked storage systems, e.g. storage area networks [SAN], network attached storage [NAS] · CPC title