AI Failure Healing System for IT Backup Recovery
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Solution Overview
Problem
Current methods for addressing recurring failures in IT environments, such as data backup and recovery operations, are inefficient and time-consuming, often requiring extensive manual intervention and involving multiple parties, leading to prolonged troubleshooting cycles and potential backlogs in support ticketing systems.
Innovation Solution
A system and method utilizing machine learning and artificial intelligence to identify and deploy solutions for recurring failures within IT environments, reducing the need for manual intervention by using a 'no-gap data protection' approach that includes a failure healing system, failure healing agents, and a failure solution repository to expedite the resolution of persistently occurring issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual troubleshooting processes are used to address recurring failures, then support personnel can investigate and resolve issues, but the turnaround time increases and productivity decreases
Solution Approach 1:
The system implements self-service through automated failure analysis and resolution. The failure analysis module automatically analyzes failure data from multiple sources, and the resolution module autonomously generates and applies fixes without requiring manual intervention from support personnel for routine issues.
Solution Approach 2:
The system performs preliminary actions by pre-processing failure data, maintaining a knowledge base of known failures and solutions, and preparing resolution strategies in advance. When a failure occurs, the system has already have analysis frameworks and potential solutions ready, reducing the time to resolve the issue.
2Measurement precision
If extensive manual investigation is performed to troubleshoot recurring failures, then thorough analysis can be conducted, but the time required for resolution increases
Solution Approach 1:
The system segments the failure analysis process into distinct automated modules: data collection from multiple sources, failure pattern recognition, root cause analysis, and solution generation. Each module processes specific aspects independently and efficiently, maintaining analysis accuracy while reducing overall time through parallel processing.
Solution Approach 2:
The system replaces manual mechanical investigation processes with automated computational analysis. Machine learning algorithms and automated scripts substitute for human analysts, performing data processing, pattern recognition, and solution generation at speeds impossible for manual processes while maintaining or improving accuracy through systematic analysis.
3Adaptability or versatility
If multiple parties are involved in troubleshooting recurring failures, then comprehensive expertise can be applied, but the complexity of the process increases
Solution Approach 1:
The system implements a universal multi-functional platform that consolidates the roles of multiple parties into a single integrated system. The failure analysis module handles data collection, analysis, and interpretation that previously required multiple specialists, while the resolution module generates and implements fixes across different failure types, reducing process complexity while maintaining comprehensive expertise through automated multi-functionality.
Data Source
AI summary
A method and system for intelligently resolving failures recurring in information technology (IT) environments. Specifically, the method and system disclosed herein may be directed to the resolution of persistently-occurring failures observed in data backup and/or data recovery operations. Further, resolution of any given persistently-occurring failure may entail the identification of zero, one, or more solutions (e.g., patches and/or other instructions) based on the analyses of failure-related information and host-related configuration information using machine learning and/or artificial intelligence paradigms. In cases where zero solutions are identified, the conventional and manual investigative route by way of support ticketing may be pursued.