Automated defect identification and resolution

• US 9,202,167 B1
• Filed: 06/27/2013
• Issued: 12/01/2015
• Est. Priority Date: 06/27/2013
• Status: Active Grant

• Current Assignee: Emc IP Holding Company LLC (Dell Technologies Inc.)
• Original Assignee: EMC Corporation (Dell Technologies Inc.)
• Inventors: Chamness, Mark, Schnegelberger, Eric
• Primary Examiner(s): CHEN, ALAN S
• Application Number:
  US13/928,937
• Time in Patent Office: 887 Days
• US Class Current: 1/1
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 3/08 Learning methods

Abstract

A method, article of manufacture, and apparatus for identifying and resolving defects in multiple clusters based on a reported defect instance is discussed. Computer systems may be grouped into clusters. A report of a defective system may be received, and the defective system'"'"'s cluster may be identified. A defect solution may then be distributed to all the systems in that cluster.

Claims

1. A method for resolving defects in a computer system, the method comprising:

receiving system data from a plurality of computer systems, said system data comprising system configuration data and system performance data;

storing the system data on a non-transitory computer readable storage medium;

clustering the computer systems based on at least a portion of the system data in order to obtain a plurality of clusters;

receiving a defect report for a defective system in the plurality of computer systems; and

resolving the defect, including by;

identifying which one of the plurality of clusters includes the defective system; and

comparing (1) system configuration data associated with the cluster that includes the defective system against (2) system configuration data associated with a second cluster that is different from the cluster that includes the defective system.

2. The method as recited in claim 1, wherein the system performance data includes CPU utilization, memory utilization, non-transitory computer readable medium capacity, and network bandwidth.

3. The method as recited in claim 1, wherein the system configuration data includes network topology data.

4. The method as recited in claim 1, wherein clustering the computer systems comprises applying a k-means algorithm to the system data.

5. The method as recited in claim 1, further comprising identifying additional computer systems in a same cluster as the defective system.

6. The method as recited in claim 5, further comprising distributing a defect solution to all the additional computer systems in the same cluster.

7. The method as recited in claim 6, wherein the defect solution includes an optimized system configuration.

8. The method of claim 1, wherein resolving the defect comprises distributing a system patch.

9. The method of claim 1, wherein resolving the defect comprises distributing an optimized system configuration.

10. The method as recited in claim 1, wherein:

the system performance data includes one or more of the following;

processor utilization or storage utilization;

clustering includes clustering based at least in part on performance using one or more of the following;

(1) processor utilization or (2) storage utilization from the system performance data; and

the second cluster has one or more of the following properties;

(1) the processor utilization of computer systems in the second cluster is less than the processor utilization of computer systems in the cluster that includes the defective system or (2) the storage utilization of computer systems in the second cluster is less than the storage utilization of computer systems in the cluster that includes the defective system.

11. A system for resolving defects in a computer system, the system comprising:

a repository configured to receive system data from a plurality of computer systems, said system data comprising system configuration data and system performance data, wherein the repository includes a computer readable storage medium and a processor configured to;

store the system data on the computer readable storage medium;

cluster the computer systems based on at least a portion of the system data in order to obtain a plurality of clusters;

receive a defect report for a defective system in the plurality of computer systems; and

resolve the defect, including by;

identifying which one of the plurality of clusters includes the defective system; and

comparing (1) system configuration data associated with the cluster that includes the defective system against (2) system configuration data associated with a second cluster that is different from the cluster that includes the defective system.

12. The system as recited in claim 11, wherein clustering the computer systems comprises applying a k-means algorithm to the system data.

13. The method system as recited in claim 11, wherein the processor is further configured to identify additional computer systems in a same cluster as the defective system.

14. The system as recited in claim 13, wherein the processor is further configured to distribute a defect solution to all the additional computer systems in the same cluster.

15. The system as recited in claim 14, wherein the defect solution includes an optimized system configuration.

16. The system as recited in claim 11, wherein:

the system performance data includes one or more of the following;

processor utilization or storage utilization;

clustering includes clustering based at least in part on performance using one or more of the following;

(1) processor utilization or (2) storage utilization from the system performance data; and

the second cluster has one or more of the following properties;

(1) the processor utilization of computer systems in the second cluster is less than the processor utilization of computer systems in the cluster that includes the defective system or (2) the storage utilization of computer systems in the second cluster is less than the storage utilization of computer systems in the cluster that includes the defective system.

17. A computer program product for resolving defects in a computer system, the computer program product being embodied in a non-transitory computer readable storage medium and comprising computer instructions for:

receiving system data from a plurality of computer systems, said system data comprising system configuration data and system performance data;

storing the system data on a non-transitory computer readable storage medium;

clustering the computer systems based on at least a portion of the system data in order to obtain a plurality of clusters;

receiving a defect report for a defective system in the plurality of computer systems; and

resolving the defect, including by;

identifying which one of the plurality of clusters includes the defective system; and

comparing (1) system configuration data associated with the cluster that includes the defective system against (2) system configuration data associated with a second cluster that is different from the cluster that includes the defective system.

18. The computer program product as recited in claim 17, wherein clustering the computer systems comprises applying a k-means algorithm to the system data.

19. The computer program product as recited in claim 17, further comprising computer instructions for identifying additional computer systems in a same cluster as the defective system.

20. The computer program product as recited in claim 19, further comprising computer instructions for distributing a defect solution to all the additional computer systems in the same cluster.

21. The computer program product as recited in claim 20, wherein the defect solution includes an optimized system configuration.

22. The computer program product as recited in claim 17, wherein:

the system performance data includes one or more of the following;

processor utilization or storage utilization;

the computer instructions for clustering include computer instructions for clustering based at least in part on performance using one or more of the following;

(1) processor utilization or (2) storage utilization from the system performance data; and

the second cluster has one or more of the following properties;

(1) the processor utilization of computer systems in the second cluster is less than the processor utilization of computer systems in the cluster that includes the defective system or (2) the storage utilization of computer systems in the second cluster is less than the storage utilization of computer systems in the cluster that includes the defective system.