Automated defect and optimization discovery

• US 9,911,083 B2
• Filed: 05/09/2016
• Issued: 03/06/2018
• Est. Priority Date: 06/27/2013
• Status: Active Grant

• Current Assignee: Emc IP Holding Company LLC (Dell Technologies Inc.)
• Original Assignee: Emc IP Holding Company LLC (Dell Technologies Inc.)
• Inventors: Chamness, Mark, Schnegelberger, Eric
• Primary Examiner(s): CHEN, ALAN S
• Application Number:
  US15/150,237
• Publication Number:
  US 20160314412A1
• Time in Patent Office: 666 Days
• Field of Search: None
• CPC Class Codes: G06F 11/0751 Error or fault detection not based on redundancy power supply failures G06F1/30; network fault management H04L41/06
• CPC Class Codes: G06F 11/08 Error detection or correction by redundancy in data representation, e.g. by using checking codes
• CPC Class Codes: G06F 11/3409 for performance assessment
• CPC Class Codes: G06F 11/3476 Data logging G06F11/14, G06F11/2205 take precedence
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 3/08 Learning methods

Abstract

Performance information and configuration information is received for the plurality of computer systems. The computer systems are grouped into a plurality of clusters based at least in part on the performance information, where the plurality of clusters includes a first cluster and a second cluster. A system configuration associated with the first cluster is automatically identified from the configuration information and is automatically sent to the second cluster.

Claims

1. A computer-implemented method, comprising:

receiving, for a plurality of computer systems, performance information and configuration information, wherein the performance information includes an amount of processing capacity utilized and an amount of storage capacity utilized, wherein a lower amount of processing capacity utilized and a lower amount of storage capacity utilized are associated with a healthier cluster;

grouping the plurality of computer systems into a plurality of clusters based at least in part on the performance information, wherein the plurality of clusters includes a first cluster and a second cluster, wherein the first cluster is healthier than the second cluster, and wherein a priority list is generated based on health of the plurality of computer systems of each cluster;

automatically identifying a system configuration associated with the first cluster from the configuration information; and

automatically sending the system configuration associated with the first cluster to a second cluster to allow computer systems of the second cluster to configure themselves based on the system configuration.

2. The method of claim 1, wherein the system configuration includes network topology.

3. The method of claim 1, wherein an unhealthier cluster has a higher priority in the priority list than a healthier cluster.

4. The method of claim 1, wherein the priority list is generated based at least in part on a number of computers systems, such that a cluster with more computer systems has a higher priority in the priority list than a cluster with fewer computer systems.

5. The method of claim 1, wherein one or more computer systems of the second cluster are reconfigured based on the system configuration associated with the first cluster.

6. The method of claim 1, wherein a computer system having a health higher than a predetermined threshold is grouped into the first cluster.

7. A non-transitory machine-readable medium having instructions stored therein, which when executed by a processor, cause the processor to perform operations, the operations comprising:

receiving, for a plurality of computer systems, performance information and configuration information, wherein the performance information includes an amount of processing capacity utilized and an amount of storage capacity utilized, wherein a lower amount of processing capacity utilized and a lower amount of storage capacity utilized are associated with a healthier cluster;

grouping the plurality of computer systems into a plurality of clusters based at least in part on the performance information, wherein the plurality of clusters includes a first cluster and a second cluster, wherein the first cluster is healthier than the second cluster, and wherein a priority list is generated based on health of the plurality of computer systems of each cluster;

automatically identifying a system configuration associated with the first cluster from the configuration information; and

automatically sending the system configuration associated with the first cluster to a second cluster to allow computer systems of the second cluster to configure themselves based on the system configuration.

8. The machine-readable medium of claim 7, wherein the system configuration includes network topology.

9. The machine-readable medium of claim 7, wherein an unhealthier cluster has a higher priority in the priority list than a healthier cluster.

10. The machine-readable medium of claim 7, wherein the priority list is generated based at least in part on a number of computers systems, such that a cluster with more computer systems has a higher priority in the priority list than a cluster with fewer computer systems.

11. The machine-readable medium of claim 7, wherein one or more computer systems of the second cluster are reconfigured based on the system configuration associated with the first cluster.

12. The machine-readable medium of claim 7, wherein a computer system having a health higher than a predetermined threshold is grouped into the first cluster.

13. A data processing system, comprising:

a processor; and

a memory storing instructions, when executed by the processor, cause the processor to perform operations, the operations including

receiving, for a plurality of computer systems, performance information and configuration information, wherein the performance information includes an amount of processing capacity utilized and an amount of storage capacity utilized, wherein a lower amount of processing capacity utilized and a lower amount of storage capacity utilized are associated with a healthier cluster,

grouping the plurality of computer systems into a plurality of clusters based at least in part on the performance information, wherein the plurality of clusters includes a first cluster and a second cluster, wherein the first cluster is healthier than the second cluster, and wherein a priority list is generated based on health of the plurality of computer systems of each cluster,

automatically identifying a system configuration associated with the first cluster from the configuration information, and

automatically sending the system configuration associated with the first cluster to a second cluster to allow computer systems of the second cluster to configure themselves based on the system configuration.

14. The system of claim 13, wherein the system configuration includes network topology.

15. The system of claim 13, wherein an unhealthier cluster has a higher priority in the priority list than a healthier cluster.

16. The system of claim 13, wherein the priority list is generated based at least in part on a number of computers systems, such that a cluster with more computer systems has a higher priority in the priority list than a cluster with fewer computer systems.

17. The system of claim 13, wherein one or more computer systems of the second cluster are reconfigured based on the system configuration associated with the first cluster.

18. The system of claim 13, wherein a computer system having a health higher than a predetermined threshold is grouped into the first cluster.