Disaster Recovery Framework Using Disruption Tolerance Matrix
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Solution Overview
Problem
Existing solutions for disaster recovery and continuity in IT systems are not flexible or cost-effective, as they often require a monolithic approach that does not account for varying data loss tolerance, recovery time requirements, and geographic distances between primary and secondary sites, making them unsuitable for all enterprises.
Innovation Solution
A vendor-agnostic framework that evaluates business processes and IT assets using a three-dimensional disruption tolerance matrix, allowing for flexible and cost-effective solutions tailored to specific sub-systems and data classes, considering data loss tolerance, recovery time, and geographic distance between sites.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a monolithic disaster recovery solution is implemented across the entire IT system, then the most stringent requirements are addressed, but the solution is not cost effective since not all assets necessitate the most stringent solution
Solution Approach 1:
The patent segments the enterprise IT system into multiple functional sub-systems and data classes, evaluating each against the disruption tolerance matrix separately. This allows different disaster recovery solutions to be applied to different segments based on their specific requirements, rather than applying a uniform monolithic solution across the entire system.
Solution Approach 2:
The patent applies local quality by tailoring the disaster recovery solution to each functional sub-system and data class based on its specific disruption tolerance characteristics. Each segment receives a customized solution matched to its actual business impact and tolerance levels, rather than a one-size-fits-all approach.
2Ease of manufacture
If scheduled tape-backups are used, then cost is reduced, but data loss of one minute or one second may be unacceptable to some enterprises
Solution Approach 1:
The patent changes the parameters of the disaster recovery solution by introducing the disruption tolerance matrix with three dimensions: data loss tolerance, recovery time requirement, and geographic distance. This allows the system to select appropriate solutions ranging from tape backups for tolerant applications to continuous replication for intolerant applications, optimizing both cost and data protection.
3Ease of manufacture
If recovery time is extended to several hours or days for tape backup retrieval, then cost is reduced, but some enterprises need to resume operations within seconds
Solution Approach 1:
The patent introduces dynamics by making the disaster recovery solution adaptable to different recovery time requirements through the disruption tolerance matrix. The system dynamically selects between slow, inexpensive solutions like tape backups and fast, expensive solutions like continuous replication, based on each functional sub-system's actual recovery time needs.
4Device complexity
If a single category of solution is applied to all enterprises, then implementation is simplified, but the solution does not fit all enterprises with varying requirements
Solution Approach 1:
The patent achieves universality by creating a multi-functional framework that can accommodate diverse disaster recovery needs within a single evaluation system. The disruption tolerance matrix serves as a universal tool that guides selection of appropriate solutions for different enterprise types and requirements, making the approach broadly applicable while maintaining customization.
Data Source
AI summary
A framework and method for use in determining appropriate information technology system disaster recovery and operational continuity solutions for an enterprise. In one embodiment the method includes identifying (504) business processes associated with achieving a defined mission of the enterprise. Assets of the information technology system are grouped (508) into one or more functional sub-system/data class groups and one or more of the business processes are selected. The functional sub-system/data class groups are mapped (524) to the selected business processes to establish a correspondence between each selected business process and one or more of the functional sub-system/data class groups. Thereafter, each functional sub-system/data class group corresponding with each selected business process is associated (602) with a solution class included in a three-dimensional disruption tolerance decision matrix.