Policy Simulation for Proactive IT Service Management
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Solution Overview
Problem
Current IT service operations management technologies are reactive and lack systemic What-If analysis capabilities, failing to recognize the interrelation between policies, patterns of behavior, and events in production support engagement, leading to challenges in formulating effective policy decisions.
Innovation Solution
A system and method that configures a knowledge base with policies, reference events, and scenarios, using an agent-based simulation model to select and optimize policies that meet service level agreements (SLAs) by simulating and processing relevant policies to identify optimal candidates for implementation in production support engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If current reactive technologies are used for IT service operations management, then existing dashboards and KPI tracking are provided, but the system lacks proactive policy formulation capability and cannot perform What-If analysis
Solution Approach 1:
The system pre-configures a knowledge base containing multiple policies, reference events, and reference scenarios before actual incidents occur. When an incident is detected, the system retrieves pre-defined policies and simulates their effects in advance to determine the optimal policy response, enabling proactive policy formulation rather than reactive responses
Solution Approach 2:
The system introduces a simulation module as an intermediary between incident detection and policy selection. This simulation module virtualizes the production support environment and applies candidate policies to reference scenarios to predict outcomes, thereby enabling What-If analysis without affecting actual production systems
2Reliability
If multiple policies are simulated and optimized to meet SLA requirements, then optimal policy selection is improved, but the processing time and computational resources increase
Solution Approach 1:
The system pre-simulates multiple policies against reference scenarios and stores the results in the knowledge base. When a real incident occurs, the system retrieves pre-computed simulation results for matching scenarios, significantly reducing the time needed to select optimal policies while maintaining SLA compliance
Solution Approach 2:
The system creates virtual copies of the production support environment through simulation models. These copies allow extensive policy testing and optimization without consuming actual production resources or time, enabling thorough policy evaluation while maintaining fast response times in the real system
3Reliability
If the system provides comprehensive monitoring and control capabilities, then situation handling is improved, but the system complexity and difficulty of operation increase
Solution Approach 1:
The system automatically detects incidents, retrieves relevant policies from the knowledge base, simulates their effects, and selects optimal policies without requiring manual intervention. This self-service capability maintains comprehensive monitoring and control while simplifying operation for users who simply need to report incidents
Data Source
AI summary
A system and method for selecting an optimal policy to be implemented in production support engagement. The system configures a knowledge base including plurality of policies, reference events, and reference scenarios. The plurality of policies is mapped with the plurality of reference scenarios and the plurality of reference events. The plurality of policies is defined in a plurality of layers in a manner that each policy corresponds to a particular layer of the plurality of layers. Relevant policies, out of the plurality of policies, may be selected based on an event received. Simulation may be performed on the relevant policies for identifying first candidate policy. The optimization may be performed on the relevant policies for identifying second candidate policy. The first and second candidate policy indicate the optimal policy to be implemented in the production support engagement.