Data Protection Policy Migration via Common Schema
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Solution Overview
Problem
Current data protection methods require complex and time-consuming configuration of data protection policies across different applications, leading to inefficiencies in resource management and policy migration, due to varied parameter sets, terminology, and user interfaces.
Innovation Solution
A computer system utilizing a policy generator that translates user input into a common data protection requirements specification (DPRS) schema, allowing for the generation of standardized data protection policies across different applications, simplifying configuration and policy translation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a volume backup is performed to protect complete data, then restoration speed is improved, but storage resource consumption increases
Solution Approach 1:
The patent segments the backup approach by offering two distinct modes: volume backup for complete data protection with fast restoration, and file-by-file backup for selective protection with reduced storage consumption. Users can choose the appropriate segmentation level based on their specific needs.
Solution Approach 2:
The patent applies local quality by allowing different backup strategies for different data portions. File-by-file backup enables selective protection of only critical files, while volume backup protects entire volumes. This localized approach optimizes both storage consumption and restoration speed for specific data regions.
2Quantity of substance
If file-by-file backup is performed to protect only application-related files, then storage space consumption is reduced, but restoration time increases
Solution Approach 1:
The patent applies partial action by implementing file-by-file backup that protects only the specific application-related files needed, rather than backing up entire volumes. This partial approach reduces storage space consumption while accepting longer restoration times for selective file recovery.
3Manufacturing precision
If complex configuration parameters are used to customize data protection policies, then policy precision is improved, but configuration complexity increases
Solution Approach 1:
The patent implements universality by creating a standardized policy template system that can be applied across multiple data protection scenarios. Pre-defined templates cover common protection needs, allowing administrators to achieve precise policy configuration without navigating complex parameter sets for each unique scenario.
Solution Approach 2:
The patent applies preliminary action by providing pre-configured policy templates that contain commonly needed protection parameters already set. Administrators can start with these pre-prepared templates and make minimal adjustments, rather than configuring every parameter from scratch, thereby reducing configuration complexity while maintaining policy precision.
4Adaptability or versatility
If different data protection applications are used to meet diverse protection needs, then adaptability is improved, but configuration time increases
Solution Approach 1:
The patent implements universality by designing a standardized policy template system that can be applied across different data protection applications and scenarios. This universal template approach allows the same configuration framework to serve multiple protection needs, reducing the time required to configure policies across diverse applications.
Data Source
AI summary
Computer systems and methods for protecting data. A computer system includes a processor, a policy generator, and resources. Each resource has associated data. The processor accesses a data protection requirements specification (DPRS). The DPRS uses a common, non-application specific schema to represent first and second schema for expressing data protection policies. The processor triggers the policy generator to generate a first data protection policy for protecting a resource. The processor uses the first data protection policy to protect data associated with the resource. To generate the first data protection policy, the policy generator scans the DPRS and identifies elements of the DPRS. The elements of the DPRS are pre-defined in the common schema. The policy generator translates values of the elements to corresponding attributes of the first data protection policy expressed in the first schema. A value of a first element in the common schema corresponds to the resource to be protected.