Predictive Analytics for IT System Failure Anticipation
Solution Overview
Problem
Current IT system monitoring tools fail to predict system failures and SLA violations effectively, as they operate in isolation and do not consider the impact of environmental changes on system behavior, leading to inadequate predictive capabilities.
Innovation Solution
A system and method that receives and analyzes a stream of data representing statistical parameters to construct a statistical model, applying pre-stored rules and threshold values to predict system behavior, with a feedback loop for dynamic updates in response to pattern deviations, enabling real-time predictive analytics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple monitoring tools are used in isolation for system analysis, then each tool can perform its specific function, but the overall predictive capability remains insufficient
Solution Approach 1:
The patent combines multiple monitoring tools (performance monitoring, network monitoring, application monitoring) into a unified predictive analytics system that integrates their data streams and analytical capabilities, enabling comprehensive system-wide predictions rather than isolated tool functions
Solution Approach 2:
The predictive analytics system serves multiple functions simultaneously: it performs statistical analysis, pattern recognition, anomaly detection, and predictive forecasting across diverse IT infrastructure components, making a single system capable of replacing multiple specialized tools
2Adaptability or versatility
If manually set thresholds are used for SLA violation detection, then implementation is simple, but the system cannot adapt to environmental changes and behavioral patterns
Solution Approach 1:
The system dynamically adjusts thresholds and parameters based on real-time environmental conditions and learned behavioral patterns, transitioning from static manual thresholds to adaptive dynamic thresholds that evolve with system behavior
Solution Approach 2:
The system implements feedback loops where prediction results and actual system behavior are continuously compared, and this feedback is used to refine statistical models, adjust parameters, and improve future predictions, creating a self-learning mechanism
3Speed
If statistical analysis is performed on historical data, then predictive insights can be gained, but real-time adaptation to new patterns is delayed
Solution Approach 1:
The system performs preliminary statistical analysis on historical data to establish baseline behavioral patterns and relationships before real-time operation, pre-computing statistical models that can quickly evaluate current system state against established patterns
Solution Approach 2:
The system maintains continuous statistical analysis operations, continuously updating predictions and model parameters as new data arrives, ensuring uninterrupted real-time monitoring and adaptation without periodic batch processing delays
Data Source
AI summary
Disclosed is a method and apparatus for organizing, correlating IT management data in batch mode as well as real time and doing predictive analytics to indicate possible threshold breaches, possible failures and usage bottlenecks in the systems in an information technology (IT) environment. The system and method further predicts the state of the information technology (IT) system components systematically based on current and past system states and system component states, overall systemic behavior, known system behavioral rules and load conditions/usage characteristics.