Infrastructure Change Guidance System for Failure Prediction
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Solution Overview
Problem
The implementation of infrastructure changes in IT systems is often risky and labor-intensive, leading to disruptive failures due to the complexity of tracking and monitoring these changes, which can result in infrastructure roll-backs and other failure modes.
Innovation Solution
A guidance system that utilizes advanced data analytics to predict and prescribe the right flow for successful infrastructure changes by identifying distinct clusters of representative changes in a failure mode analysis parameter space, providing proactive failure mode analysis and checklists to mitigate potential issues, and integrating with existing change management processes to reduce errors and manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional manual methods are used to track and monitor infrastructure changes, then implementation flexibility is maintained, but the likelihood of successful change execution decreases and disruptive failures increase
Solution Approach 1:
The patent introduces an intermediary system comprising a failure mode analysis model and guidance circuitry that mediates between the proposed infrastructure change and the actual execution. This intermediary analyzes the change parameters, predicts potential failures, and provides guidance without requiring complete manual tracking of all change aspects, thus improving reliability while managing complexity.
Solution Approach 2:
The system performs preliminary failure mode analysis before the actual infrastructure change is executed. By predicting potential failures in advance and providing guidance on how to avoid them, the system prevents issues before they occur, thereby improving the success rate without requiring complex real-time monitoring during execution.
2Measurement precision
If comprehensive tracking and monitoring of infrastructure changes is implemented, then failure prediction accuracy improves, but resource consumption and manual intervention increase
Solution Approach 1:
The failure mode analysis model operates autonomously by self-evaluating proposed infrastructure changes against historical data and failure patterns. The system serves itself by automatically analyzing change parameters, generating failure predictions, and providing guidance without requiring manual resource allocation for each analysis, thus maintaining high prediction accuracy while improving resource efficiency.
Solution Approach 2:
The patent replaces manual tracking and monitoring mechanisms with an automated data analytics system. The failure mode analysis model uses computational algorithms to analyze change parameters and predict failures, substituting mechanical human effort with automated electronic processing, thereby maintaining measurement precision while reducing resource consumption.
3Productivity
If manual review processes are used for infrastructure changes, then implementation simplicity is maintained, but error rates increase and execution time extends
Solution Approach 1:
The system implements feedback by analyzing the results of past infrastructure changes and using this information to improve future predictions. The failure mode analysis model continuously learns from historical data, providing increasingly accurate failure predictions and guidance. This feedback mechanism reduces error rates while maintaining fast automated execution, as the system becomes more accurate over time without requiring manual review of each change.
Data Source
AI summary
All modern enterprises rely completely on the continual correct execution of hardware and software resources that constitute the information technology (IT) infrastructure environment for the business. At the same time, hardware and software resources continually evolve, and the enterprise must often make changes to its infrastructure to incorporate the new or updated hardware and software resources. These changes are risky, and failure to properly execute the changes can result in infrastructure roll-backs and other failure modes that are often very disruptive to the enterprise. A guidance system for changes in infrastructure increases the likelihood of successful implementation of the changes. In some implementations, for example, the guidance system provides clear guidelines and checklists that depict success criteria, along with a scoring interface that pro-actively indicates the factors that can go wrong, and how to mitigate and plan for the factors in advance.