Detecting hardware and software problems in remote systems

• US 9,817,742 B2
• Filed: 06/25/2013
• Issued: 11/14/2017
• Est. Priority Date: 06/25/2013
• Status: Active Grant

• Current Assignee: Dell International LLC (Dell Technologies Inc.)
• Original Assignee: Dell International LLC (Dell Technologies Inc.)
• Inventors: Hankins, Ryan
• Primary Examiner(s): NGUYEN, CAM LINH T
• Application Number:
  US13/925,910
• Publication Number:
  US 20140379714A1
• Time in Patent Office: 1,603 Days
• Field of Search: 707690, 707737
• CPC Class Codes: G06F 11/0706 the processing taking place on a specific hardware platform or in a specific software environment
• 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 11/3055 Monitoring arrangements for monitoring the status of the computing system or of the computing system component, e.g. monitoring if the computing system is on, off, available, not available error or fault processing without redundancy G06F11/0703; error detection or correction by redundancy in data representation G06F11/08; error detection or correction by redundancy in operation G06F11/14; error detection or correction by redundancy in hardware G06F11/16
• CPC Class Codes: G06F 11/3082 the data filtering being achieved by aggregating or compressing the monitored data
• CPC Class Codes: G06F 2201/88 Monitoring involving counting

Abstract

A method for detecting hardware and/or software anomalies in remote systems. The method may include aggregating, in a centralized electronic database, by an electronic database server, data received via a network from each of the remote systems, the data relating to operating statistics of one or more subcomponents of the remote systems over time. The method may also include utilizing an electronic database client communicatively coupled to the centralized database to automatically periodically access and analyze data stored in the centralized database to identify anomalies in hardware and/or software components of the remote systems. In one embodiment, the data relating to operating statistics of the subcomponents may include data from statistics counters corresponding to the subcomponents, each statistics counter, in one state, indicative of an identifiable error. In this regard, analyzing data stored in the centralized database may involve comparing data from the statistics counters to identify the anomalies.

Claims

1. A method for detecting hardware and/or software anomalies in remote systems, the method comprising:

aggregating, in a centralized electronic database, by an electronic database server, data received via a network from each of the remote systems, the data relating to operating statistics of each of one or more subcomponents of the remote systems over time, each remote system being separate and operably independent from the other remote systems and comprising a data storage system having a data storage system controller and a data storage device;

utilizing an electronic database client communicatively coupled to the centralized electronic database to automatically periodically access and analyze data stored in the centralized electronic database to identify anomalies in at least one of hardware and/or software components of one or more of the remote systems; and

applying one or more false positive rules to the identified anomalies to detect a falsely identified anomaly, and where a falsely identified anomaly is detected, overriding the identification of the falsely identified anomaly as an anomaly;

wherein the data relating to operating statistics of each of one or more subcomponents of the remote systems over time comprises data from statistics counters corresponding to the one or more subcomponents, each statistics counter with a non-zero count value identifying an occurrence of an error.

2. The method of claim 1, wherein the remote systems each comprise at least one network adapter.

3. The method of claim 1, further comprising, for each remote system, aggregating data received from each of the one or more subcomponents thereof in a database local to the respective remote system.

4. The method of claim 3, wherein aggregating data received via a network from each of the remote systems comprises receiving, via the network, replicated data from each of the local databases of each remote system.

5. The method of claim 4, further comprising, for each of the one or more subcomponents of a remote system, collecting operating statistics associated with the respective subcomponent for reporting to the database local to the remote system of which the subcomponent is a part.

6. The method of claim 1, wherein aggregating data received via a network from each of the remote systems comprises receiving data from the remote systems on a periodic basis.

7. The method of claim 1, wherein aggregating data received via a network from each of the remote systems comprises receiving data from the remote systems on-demand, at the request of the database server.

8. The method of claim 1, wherein aggregating data received via a network from each of the remote systems comprises receiving data from the remote systems upon request of a user-operator.

9. The method of claim 1, wherein analyzing data stored in the centralized electronic database to identify anomalies comprises comparing data from the statistics counters to identify the anomalies.

10. The method of claim 9, further comprising defining rules for application against the data in the centralized electronic database, the rules designed to identify anomalies in the at least one of the hardware and/or software components of one or more of the remote systems, wherein analyzing data stored in the centralized electronic database to identify anomalies comprises applying the rules to the data stored in the centralized electronic database.

11. The method of claim 1, further comprising utilizing the electronic database client to access and automatically analyze, at the request of a user-operator, data stored in the centralized electronic database to identify anomalies in the at least one of hardware and/or software components of one or more of the remote systems.

12. The method of claim 1, further comprising generating and outputting a visual report of identified anomalies.

13. The method of claim 1, further comprising automatically taking measures to resolve a failure in at least one of the hardware and/or software components of a remote system identified as associated with an anomaly.

14. An information handling system comprising:

a plurality of remote systems, each remote system being separate and operably independent from the other remote systems and comprising a data storage system having a data storage system controller, a data storage device, and at least one network adapter;

an electronic database server communicatively coupled with the plurality of remote systems, the electronic database server comprising a centralized electronic database associated with the remote systems and storing data received via a network from the plurality of remote systems relating to operating statistics of each of one or more subcomponents of the plurality of remote systems over time; and

an electronic database client communicatively coupled to the electronic database server and configured to automatically periodically access and analyze data stored in the centralized electronic database to identify anomalies in at least one of hardware and/or software components of one or more of the plurality of remote systems; and

one or more false positive rules configured to detect a falsely identified anomaly, and where a falsely identified anomaly is detected, override the identification of the falsely identified anomaly as an anomaly;

wherein the data relating to operating statistics of each of one or more subcomponents of the plurality of remote systems over time comprises data from statistics counters corresponding to the one or more subcomponents.

15. The information handling system of claim 14, further comprising, for each remote system, a database local to the respective remote system for aggregating data received from each of the one or more subcomponents thereof.

16. The information handling system of claim 15, wherein the data stored in the centralized electronic database is replicated from the local databases of each remote system.

17. The information handling system of claim 14, wherein the electronic database client is configured to analyze data stored in the centralized electronic database to identify anomalies by comparing data from the statistics counters to identify the anomalies.

18. A method for detecting hardware and/or software anomalies in remote systems, the method comprising:

aggregating, in a centralized electronic database, by an electronic database server, data received via a network from each of the remote systems, the data relating to operating statistics of each of one or more subcomponents of the remote systems over time, each remote system being separate and operably independent from the other remote systems and comprising a data storage system having a data storage system controller and a data storage device; and

utilizing an electronic database client communicatively coupled to the centralized electronic database to automatically periodically access and analyze data stored in the centralized electronic database to identify anomalies in at least one of hardware and/or software components of one or more of the remote systems; and

applying one or more false positive rules to the identified anomalies to detect a falsely identified anomaly, and where a falsely identified anomaly is detected, overriding the identification of the falsely identified anomaly as an anomaly;

wherein the data relating to operating statistics of each of one or more subcomponents of the remote systems over time comprises data from statistics counters corresponding to the one or more subcomponents.