Storage Domain Risk Analysis via Downtime Cost Mapping
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Solution Overview
Problem
Current data storage systems lack comprehensive risk analysis and management tools to assess downtime costs and failure points across software application and storage domains, leading to inefficiencies in data path monitoring and storage capacity utilization.
Innovation Solution
A domain management process that selects components from both domains, simulates failures, and disseminates downtime costs and failure points to users, enabling comprehensive risk analysis, performance evaluation, and data path characterization, while constraining access to enhance storage efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If comprehensive risk analysis and management tools are implemented across software application and storage domains, then system reliability and security characterization are improved, but device complexity and implementation cost increase
Solution Approach 1:
The system is divided into distinct domains (software application domain and storage domain) with separate management processes for each. The risk analysis tool selectively analyzes specific portions of the storage system rather than the entire system, breaking down the complex analysis task into manageable segments that can be processed independently.
Solution Approach 2:
The risk analysis is applied locally to selected portions of the storage system rather than uniformly across the entire system. The management process allows selective analysis of specific components based on their importance, downtime costs, and failure points, applying different levels of analysis depth to different parts of the system.
2Measurement precision
If complete mapping of data paths is performed across both domains, then measurement precision and system characterization are improved, but loss of time and computational resources increase
Solution Approach 1:
The system performs preliminary identification and selection of critical components, data paths, and failure points before conducting the actual risk analysis. By pre-identifying which components have high downtime costs or represent single points of failure, the system can focus measurement efforts on these critical areas rather than uniformly analyzing the entire system.
Solution Approach 2:
The risk analysis tool performs analysis on selected portions of the storage system rather than attempting to analyze every component. This partial action approach focuses computational resources on the most critical components (those with high downtime costs or failure points) while omitting less critical components, achieving sufficient measurement precision without exhaustive analysis.
3Loss of information
If downtime costs are assigned and aggregated across multiple components, then loss of information about system criticality is reduced, but device complexity and processing requirements increase
Solution Approach 1:
The system merges downtime cost information from multiple individual components into aggregated totals for the entire storage system or selected portions. By combining the downtime costs of individual components that make up a data path or system portion, the tool provides a comprehensive view of system criticality without requiring separate analysis of each component's impact.
Solution Approach 2:
The risk analysis tool provides feedback to users by disseminating assigned downtime costs and aggregated totals, enabling users to understand which components and data paths are most critical to system operation. This feedback loop allows users to make informed decisions about resource allocation, redundancy planning, and risk mitigation based on the quantitative downtime cost information.
Data Source
AI summary
A method for analyzing management risk of a computer network includes selecting a portion of a storage system, determining a first downtime cost associated with a component included in the portion of the storage system, assigning the first downtime cost to the component, and disseminating the assigning of the downtime cost to a user.