Dynamic Event Routing Brokerage Service for IT Downtime Reduction
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Solution Overview
Problem
Current event resolution systems in IT systems often rely on manual processes and suboptimally select from multiple event resolution services, leading to inefficiencies and increased downtime.
Innovation Solution
A brokerage service that dynamically optimizes the routing of events to multiple solvers by classifying events into streams, solving optimization problems based on solver success rates, and applying policies to route events to the most cost-effective solvers, ensuring real-time resolution and minimizing downtime.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual activities are used to resolve IT system problems, then flexibility in handling complex issues is maintained, but resolution time increases and productivity decreases
Solution Approach 1:
The patent segments event resolution into multiple independent solvers (expert systems, automated resolution services, manual processes) that can operate in parallel. Each solver handles specific types of events, allowing simultaneous processing of multiple events and reducing overall resolution time while maintaining appropriate flexibility for complex issues through hierarchical escalation.
Solution Approach 2:
The patent introduces an event router as an intermediary component that receives events from the IT system, classifies them, and directs them to appropriate solvers. This intermediary enables automated routing and classification, reducing manual intervention time while preserving the ability to handle complex issues through appropriate solver selection.
2Reliability
If multiple event resolution services from different ISVs are utilized, then resolution capability and success rates improve, but system complexity and difficulty of management increase
Solution Approach 1:
The event router is designed as a universal component that can interface with multiple different solver types (expert systems, automated services, manual processes) from various ISVs through standardized protocols. This multi-functionality allows the system to leverage diverse resolution capabilities while maintaining a single point of management, reducing overall system complexity.
Solution Approach 2:
The patent implements feedback mechanisms where the event router monitors solver performance, success rates, and resolution times. This feedback is used to dynamically adjust routing decisions, prioritize solvers with higher success rates, and continuously optimize the system. The feedback loop simplifies management by providing visibility into solver performance and enabling data-driven decisions about resource allocation.
3Ease of manufacture
If non-optimally selected solvers are used for event resolution, then implementation simplicity is maintained, but costs increase and efficiency decreases
Solution Approach 1:
The patent implements preliminary classification and routing decisions through the event router, which analyzes incoming events and determines the most appropriate solver before dispatch. This preliminary action prevents suboptimal solver selection and ensures that events are routed to the most cost-effective and efficient resolver, improving overall productivity without significantly increasing implementation complexity.
Solution Approach 2:
The system dynamically changes routing parameters based on solver performance metrics, event characteristics, and current system state. By adjusting which solver handles which event type based on real-time performance data, the system optimizes cost efficiency and productivity while maintaining relatively simple implementation through parameter-based routing rules.
Data Source
AI summary
An approach is provided for optimally routing events in an IT system to solvers which provide resolutions of the events. Event streams originating from the IT system are defined. Events are classified into the event streams. An optimization problem is solved that minimizes costs incurred for using respective solvers based on constraints which include success rates of the solvers. Based on the solved optimization problem, policies are defined that associate the event streams to the solvers in a many-to-one correspondence. In real time, the defined policies are applied to the event streams. Based on the applied policies and the classified events, the events are routed to respective solvers. An indication is received that the events are resolved by the respective solvers, which reduces downtime in the IT system.