Cognitive Storage Troubleshooting Playbook System
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Solution Overview
Problem
Troubleshooting and auto-remediation of problems in complex storage virtualization environments are challenging due to the complexity of internal components and external relationships, and the unavailability of experts at all times.
Innovation Solution
A computer-implemented method and system that guides users through selecting applicable troubleshooting logic playbooks, asking questions to identify resolution paths, obtaining cross-domain information, and auto-remediating issues by cognitively determining possible resolutions based on user inputs and infrastructure data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If expert knowledge is used to troubleshoot storage environment problems, then problem-solving accuracy is improved, but availability is reduced because experts are not available at all times
Solution Approach 1:
The system enables self-service troubleshooting by capturing expert knowledge in playbooks and using cognitive computing to automatically diagnose and remediate storage environment problems without requiring human expert intervention, thus maintaining high accuracy while improving availability
Solution Approach 2:
Expert knowledge is captured and stored in playbooks in advance, allowing the system to prepare resolution paths beforehand. When problems occur, the pre-prepared knowledge base enables immediate automated troubleshooting without waiting for expert availability
2Reliability
If complex troubleshooting procedures are implemented to address storage environment problems, then problem resolution capability is improved, but ease of operation is reduced
Solution Approach 1:
The cognitive computing system acts as an intermediary between users and complex troubleshooting procedures. It automatically executes playbooks and resolution paths, shielding users from complexity while maintaining high problem resolution capability through structured, pre-defined procedures
Solution Approach 2:
Troubleshooting knowledge is segmented into discrete playbooks with specific resolution paths for different problem types. This segmentation allows the system to handle complexity through modular, organized procedures while presenting a simplified interface to users
3Productivity
If automated remediation is implemented to improve response time, then productivity is improved, but device complexity is increased
Solution Approach 1:
The cognitive computing system provides multi-functional capabilities including problem detection, diagnosis, resolution path selection, and automated remediation within a single platform. This universality improves productivity through rapid automated response while managing complexity through integrated design
Data Source
AI summary
Disclosed is a computer-implemented method of finding, troubleshooting and auto-remediating problems in storage environments. The method includes guiding a user, by a data processing system of an active storage environment, to select an applicable playbook of troubleshooting logic from among playbooks of different troubleshooting logic to address problem(s) with infrastructure device(s) of the active storage environment, asking the user, by the data processing system, questions from the applicable playbook to identify a possible resolution path for the problem(s), resulting in an identified resolution path, receiving, by the data processing system, answers to the questions from the user, obtaining, by the data processing system, cross-domain information regarding infrastructure device(s) potentially relevant to the problem(s), resulting in obtained cross-domain information, cognitively determining, by the data processing system, possible resolution(s) based on the answers and the obtained cross-domain information, and auto-remediating, by the data processing system, the problem(s).