Predictive Remediation for Recurring System Behavior Failures

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Solution Overview

Problem

Computer systems face recurring problematic behaviors due to changing demands or interactions among components, leading to temporary remedial actions that may become less effective over time, necessitating a proactive approach for sustained performance.

Innovation Solution

A predictive system remediation system that uses a self-healing architecture with a machine learning engine to detect problematic behaviors, predict the effectiveness of remedial actions, and apply them autonomously, even if initial predictions do not meet performance criteria, while continuously updating its models based on outcomes.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If remedial actions are applied to address problematic system behavior, then system performance is temporarily improved, but the effectiveness decreases over time and the behavior recurs

Engineering Contradiction:

Improvesystem performanceVSAvoidduration of remedial action effectiveness

Core Design Contradiction:

ReliabilityVSDuration of action of stationary object

Solution Approach 1:

The system performs preliminary actions by predicting future problematic behaviors before they occur and applying remedial actions in advance. The predictive model analyzes historical data and system patterns to identify upcoming issues, allowing the system to remediate proactively rather than reactively, thereby extending the duration of effectiveness between remedial actions.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements continuous feedback loops where the outcomes of applied remedial actions are monitored and fed back into the predictive model. This feedback mechanism allows the system to learn from past effectiveness patterns, adjust predictions, and improve the timing and selection of future remedial actions, preventing the recurrence of temporarily effective but short-lived fixes.

Inventive Principle:

Principle #23Feedback

2Speed

If the system applies remedial actions autonomously based on predictions, then system responsiveness is improved, but false applications may occur when predictions do not meet performance criteria

Engineering Contradiction:

Improvespeed of remedial action applicationVSAvoidaccuracy of remedial action application

Core Design Contradiction:

SpeedVSReliability

Solution Approach 1:

The system dynamically adjusts prediction parameters and performance thresholds based on historical data and system conditions. By changing parameters such as confidence levels, time windows, and performance criteria, the system optimizes the balance between rapid autonomous response and accurate remedial action application, reducing false applications while maintaining speed.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system employs dynamic decision-making where the threshold for autonomous remedial action application is not fixed but adapts based on system state, historical accuracy, and current performance criteria. This dynamic approach allows the system to be more aggressive when predictions are highly confident and more conservative when uncertainty is high, optimizing both speed and reliability.

Inventive Principle:

Principle #15Dynamics

3Measurement precision

If the system waits for predictions to meet performance criteria before applying remedial actions, then action accuracy is improved, but system performance deteriorates due to delayed intervention

Engineering Contradiction:

Improveprediction accuracyVSAvoidtime delay in remedial action application

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system applies partial remedial actions when predictions meet a lower threshold of accuracy, rather than waiting for complete certainty. This partial action approach addresses the most critical aspects of predicted problems immediately while continuing to monitor for confirmation of the full prediction, thereby reducing time loss while maintaining reasonable accuracy.

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The system performs preliminary remedial actions based on predictions that meet minimum performance criteria, addressing potential issues before they fully manifest. This preliminary action is followed by continuous monitoring to confirm or adjust the remediation, balancing early intervention with accuracy verification.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS11860729B2Predictive system remediation

Publication Date: 2024.01.02 ORACLE INT CORP

AI summary

Techniques for predictive system remediation are disclosed. Based on attributes associated with applications of one or more system-selected remedial actions to one or more problematic system behaviors in a system (e.g., a database system), the system determines a predicted effectiveness of one or more future applications of a remedial action to a particular problematic system behavior, as of one or more future times. The system determines that the predicted effectiveness of the one or more future applications of the remedial action is positive but does not satisfy a performance criterion. Responsive to determining that the predicted effectiveness is positive but does not satisfy the performance criterion, the system generates a notification corresponding to the predicted effectiveness not satisfying the performance criterion. The system applies the remedial action to the particular problematic system behavior, despite already determining that the predicted effectiveness does not satisfy the one or more performance criteria.