HOTSPOT IDENTIFICATION

• US 20140325290A1
• Filed: 04/30/2013
• Published: 10/30/2014
• Est. Priority Date: 04/30/2013
• Status: Active Grant

• Current Assignee: Micro Focus LLC (Open Text Corporation)
• Original Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Inventors: Gutjahr, Bernd, Schaefer, Christian, Baumecker, Klaus
• Granted Patent: US 9,195,535 B2
• Time in Patent Office: Days
• US Class Current: 714/48
• CPC Class Codes: G06F 11/0709 in a distributed system consisting of a plurality of standalone computer nodes, e.g. clusters, client-server systems
• CPC Class Codes: G06F 11/076 by exceeding a count or rate limit, e.g. word- or bit count limit
• 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 11/0793 Remedial or corrective actions recovery from an exception in an instruction pipeline G06F9/3861; by retry G06F11/1402; for recovering from a failure of a protocol instance or entity H04L69/40

Abstract

Hotspot identification can include receiving data indicating a plurality of reported events each associated with a respective number of configuration items (CIs) of a plurality of CIs and receiving data indicating a topological dependency of each of the plurality of CIs. Hotspot identification can include assigning a weight to each of the respective number of CIs, assigning a weight to CIs of the plurality of CIs having a topological dependency from the respective number of CIs, and identifying the hotspot having a weight assigned thereto that satisfies a hotspot weight threshold.

Claims

1. A method for hotspot identification, comprising:

receiving data indicating a plurality of reported events each associated with a respective number of configuration items (CIs) of a plurality of CIs;

receiving data indicating a topological dependency of each of the plurality of CIs;

assigning a weight to each of the respective number of CIs;

assigning a weight to CIs of the plurality of CIs having a topological dependency from the respective number of CIs; and

identifying the hotspot as one of the CIs having a weight assigned thereto that satisfies a hotspot weight threshold.

2. The method of claim 1, wherein the method includes calculating a weight as a product of a confidence factor and a coverage factor.

3. The method of claim 1, wherein the method includes determining a plurality of potential hotspots common to the reported events, and wherein identifying the hotspot includes identifying the hotspot from the potential hotspots.

4. The method of claim 3, wherein the plurality of potential hotspots each has an assigned weight that is a local maximum with respect to assigned weights of adjacent CIs, and wherein the adjacent CIs are CIs one hop from each of the potential hotspots according to the topological dependency.

5. The method of claim 3, wherein identifying the hotspot from the potential hotspots common to the reported events begins with a potential hotspot of the potential hotspots having comparatively less CIs depending therefrom with respect to the other potential hotspots.

6. The method of claim 1, wherein identifying the hotspot includes identifying the hotspot without using predetermined rules associated with the reported events.

7. A non-transitory machine-readable medium storing instructions for hotspot identification, executable by a processing resource to cause a computer to:

receive data indicating a plurality of reported events each associated with a respective number of configuration items (CIs) of a plurality of CIs;

receive data indicating a topological dependency of each of the plurality of CIs;

assign a weight to each of the respective number of CIs in response to receipt of the plurality of reported events;

assign a weight to CIs of the plurality of CIs having a topological dependency from the respective number of CIs;

determine a plurality of potential hotspots as CIs that are common to the plurality of reported events and each have a weight associated therewith that is a local maximum with respect to adjacent CIs, wherein adjacent CIs are one hop from each other according to the topological dependency; and

identify the hotspot as one of the plurality of potential hotspots having a weight assigned thereto that satisfies a hotspot weight threshold.

8. The medium of claim 7, wherein the instructions to determine the potential hotspots include instructions executable by the processor to utilize the topological dependency to determine the potential hotspots common to the reported events.

9. The medium of claim 7, wherein the instructions to determine the potential hotspots include instructions executable by the processor to determine based upon stored data associated with the plurality of CIs without monitoring the plurality of CIs.

10. The medium of claim 7, wherein the instructions to assign the weight to each of the respective number of CIs and the CIs having the topological dependency from the respective number of CIs include instructions executable by the processor to assign the weight as a product of a coverage factor and a confidence factor, and wherein the confidence factor is a function of a total number of the reported events that are impacted by the given CI and a total number of closures of the reported events that depend upon the given CI.

11. A system for hotspot identification, the system comprising a processing resource in communication with a non-transitory computer readable medium, wherein the non-transitory computer readable medium contains a set of instructions and wherein the processing resource is designed to carry out the set of instructions to:

receive data indicating a plurality of reported events each associated with a respective number of configuration items (CIs) of a plurality of CIs;

receive data indicating a topological dependency of each of the plurality of CIs;

calculate a respective weight as a product of a coverage factor and a confidence factor to assign to each of the respective number of CIs and CIs of the plurality of CIs having a topological dependency therefrom;

determine a plurality of potential hotspots that are common to the plurality of reported events, each of the plurality of potential hotspots having an assigned weight associated therewith that is a local maximum with respect to adjacent CIs determined using a graph representing the topological dependencies of the plurality of CIs;

identify the hotspot as one of the plurality of potential hotspots having a weight assigned thereto that satisfies a hotspot weight threshold; and

cause a display of the identified hotspot.

12. The system of claim 11, wherein the instructions to identify the hotspot include instructions executable by the processing resource to identify the hotspot without use of data obtained subsequent to the reported events.

13. The system of claim 11, wherein the instructions executable by the processing resource include instructions executable by the processing resource to perform remediation measures to the identified hotspot.

14. The system of claim 13, wherein the instructions to perform remediation measures include instructions executable by the processing resource to confirm a root cause of the reported events subsequent to performing remediation measures.

15. The system of claim 11, wherein the instructions to cause the display include instructions executable by the processor to cause the display of an ordered list of a plurality of hotspots each having a weight associated therewith satisfying the hotspot weight threshold.