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Method to Conduct Temporal Analysis for Incident Management and Problem Management in a Cloud Computing Environment

IP.com Disclosure Number: IPCOM000199345D
Publication Date: 2010-Aug-30
Document File: 2 page(s) / 20K

Publishing Venue

The IP.com Prior Art Database

Abstract

A method to conduct temporal analysis for incident management and problem management in a cloud computing environment is disclosed. The method involves using temporal event data both for predicting and preventing service incidents and for post incident analysis such as root cause analysis.

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Method to Conduct Temporal Analysis for Incident Management and Problem Management in a Cloud Computing Environment

Disclosed is a method to conduct temporal analysis for incident management and problem management in a cloud computing environment. The method involves creating a data model of events that may impact service availability. The events may include "Change Implementation" related events, "Release Implementation" related events, and "Provisioning" related events, wherein provisioning related events may include events relating to service provisioning and resource provisioning. The data model of events may further include "Scaling" related events for services and resources, "Fault and Error" related events, and "Jobs" related events.

On creating the data model of events, events at the component level, that may become service level events, are collected and aggregated. An event at the component level may become a service level event depending on one or more of the criticality of the component to the service and the criticality of the component to the event. In other words, a sub-set of the events are identified and filtered as service events. Also, a component level event may be a service event for multiple services.

Thereafter, temporal maps (traces) and visualizations of the temporal maps may be generated periodically for each IT enabled service, irrespective of the presence of service incidents. The frequency of generation depends on the complexity of the service, complexity of the infrastructure supporting the service and the number of events generated in a given time period.

Subsequently, temporal patte...