AUTOMATING DIAGNOSES OF COMPUTER-RELATED INCIDENTS

• US 20120102363A1
• Filed: 07/02/2009
• Published: 04/26/2012
• Est. Priority Date: 07/02/2009
• Status: Active Grant

• Current Assignee: Hewlett Packard Enterprise Development LP (Hewlett-Packard Enterprise Company)
• Original Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Inventors: Milojicic, Dejan S., Cox, Brian, Forell, Timothy F., Nemeth, Alan G., Connelly, Jon Christopher
• Granted Patent: US 8,868,973 B2
• Time in Patent Office: Days
• US Class Current: 714/37
• 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 11/079 Root cause analysis, i.e. error or fault diagnosis in a hardware test environment G06F11/22; in a software test environment G06F11/36
• CPC Class Codes: G06F 11/202 where processing functionality is redundant redundant communication control functionality G06F11/2005, redundant storage control functionality G06F11/2089
• CPC Class Codes: G06F 21/552 involving long-term monitoring or reporting
• CPC Class Codes: G06F 21/577 Assessing vulnerabilities and evaluating computer system security
• CPC Class Codes: G06F 2221/2101 Auditing as a secondary aspect
• CPC Class Codes: G06Q 10/0637 Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
• CPC Class Codes: H04L 69/40 for recovering from a failure of a protocol instance or entity, e.g. service redundancy protocols, protocol state redundancy or protocol service redirection management of faults, events, alarms or notifications in data switching networks H04L41/06

Abstract

A technique includes using a computer agent to observe diagnoses of computer-related incidents. Based on the observation, patterns are identified in the diagnoses, and based at least in part on the patterns, the diagnoses are selectively automated.

Claims

1. A method comprising:

observing diagnoses of computer-related incidents;

based on the observation, identifying patterns in the diagnoses; and

based at least in part on the patterns, selectively automating the diagnoses.

2. The method of claim 1, wherein the act of observing the diagnoses comprises using a computer agent to observe diagnoses of computer-related incidents by human operators.

3. The method of claim 1, wherein the acts of observing and identifying comprises using input on a candidate for automation provided by at least one human operator.

4. The method of claim 1, wherein the act of identifying comprises identifying a pattern in the diagnoses of incidents sharing a common set of symptoms, the method further comprising:

designating a diagnosis of an incident having said common set of symptoms as a candidate for automation.

5. The method of claim 4, further comprising:

increasing an automation of the candidate based at least in part on a confidence level in the diagnosis.

6. The method of claim 5, further comprising:

determining the confidence level based at least in part on observations regarding how consistently the human operators diagnose the incidents having said common set of symptoms.

7. The method of claim 5, further comprising:

determining the confidence level based on least in part on an opinion from a customer service engineer.

8. The method of claim 5, further comprising:

gradually increasing the automation as the confidence level increases.

9. The method of claim 5, further comprising:

gradually decreasing the automation as the confidence level decreases.

10. A system comprising:

a processor-based automation engine to automatically diagnose a first set of computer-related incidents;

a processor-based observation engine to observe diagnoses of a second set of computer-related incidents by human operators; and

a processor-based analysis engine to;

based on the observations, identify patterns in the diagnoses; and

based at least in part on the patterns, selectively re-designate some of the second set of computer-related problems as belonging to the first set of computer related problems.

11. The system of claim 10, wherein the analysis engine is adapted to selectively designate problems of the second set as candidates for automation.

12. The system of claim 11, wherein the analysis engine is adapted to selectively increase the automations of the candidates based on based at least in part on confidence levels of the associated diagnoses.

13. The system of claim 12, wherein the analysis engine is adapted to determine a given confidence level based at least in part on observations regarding how consistently human operators diagnose incidents that share a common set of symptoms.

14. The system of claim 12, wherein the analysis engine is adapted to determine a given confidence level based at least in part on an opinion from a customer service engineer.

15. The system of claim 10, wherein the analysis engine is adapted to re-designate some of the second set of computer-related problems as belonging to a set associated with an intermediate level of automation before being designated as belong to the first set.

16. An article comprising a computer readable storage medium to store instructions that when executed by the computer to cause the computer to:

receive data indicative of observed diagnoses of computer-related incidents;

based on the data, identify patterns in the diagnoses; and

based at least in part on the patterns, selectively designate future incidents to at least a degree of automation.

17. The article of claim 16, the storage medium storing instructions to cause the computer to receive the data from at least one human operator.

18. The article of claim 16, the storage medium storing instructions to cause the computer to receive the data from an automated computer agent.

19. The article of claim 16, the storage medium storing instructions to cause the computer to:

selectively designate the future incidents based at least in part of confidence levels associated with the diagnoses

20. The article of claim 16, the storage medium storing instructions to cause the computer to:

selectively re-designate an incident to decrease a level of automation associated with the incident.