Directory-Aware File Backup Sub-Asset Segmentation for Policy Management
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Solution Overview
Problem
Existing data backup systems face challenges in efficiently managing large assets with specialized directory services, leading to complex management of schedules, policies, and distributions, and difficulties in predictive recovery and cyber-security anomaly detection.
Innovation Solution
Implementing a file-based backup (FBB) system that utilizes metadata files to manage sub-assets with different retention and tiering policies, enabling predictive recovery and delta anomaly detection by comparing metadata files across backups.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If file-based backup systems store large assets as composite data without segmentation, then storage simplicity is maintained, but management complexity increases due to multiple schedules and policies
Solution Approach 1:
The patent segments large composite data assets into sub-assets based on directory service associations. Each sub-asset can be independently managed with its own backup schedule and policy, transforming one complex monolithic asset into multiple manageable units. This resolves the contradiction by reducing management complexity while maintaining policy flexibility through modular sub-asset structures.
Solution Approach 2:
The patent introduces a metadata file as an intermediary layer between the backup system and composite data assets. The metadata file contains directory service association information that enables automated classification and segmentation of sub-assets. This intermediary mechanism automates the segmentation process, reducing manual management complexity while preserving adaptability.
2Measurement precision
If file-based backup systems perform full asset scanning for security anomaly detection, then detection completeness is improved, but resource consumption and time requirements increase
Solution Approach 1:
The patent extracts and compares only the metadata files from successive backups instead of scanning entire composite data assets. The metadata files contain essential information about data changes and directory service associations. This extraction approach maintains anomaly detection completeness by identifying changes through metadata while dramatically reducing scanning time and resource consumption.
Solution Approach 2:
The patent performs partial scanning by focusing only on metadata files rather than complete asset scans. This partial action is sufficient for detecting anomalies and security issues because metadata contains the essential change information, thereby reducing time and resources while maintaining detection effectiveness.
3Productivity
If file-based backup systems store all backup data in single location, then storage management is simplified, but retrieval efficiency decreases for specific data segments
Solution Approach 1:
The patent segments backup storage into distributed locations based on sub-asset classification. Sub-assets associated with specific directory services are stored in locations accessible to those services, enabling efficient retrieval. This segmentation improves productivity by allowing targeted access to specific data segments while the systematic classification approach manages storage complexity.
Solution Approach 2:
The patent implements local quality by storing sub-assets in storage locations optimized for their specific access requirements. Sub-assets with directory service associations are stored where they can be efficiently retrieved by those services, improving retrieval efficiency while the organized classification structure manages storage complexity.
Data Source
AI summary
A method for managing the storage of file based backups (FBBs) includes obtaining, by a backup agent operating on a production host environment, a FBB generation request for plurality of assets at a point-in-time, wherein the backup agent is associated with a plurality of backup policies, in response to the FBB generation request: generating a FBB of the plurality of assets, performing an attribute analysis on the FBB metadata file to determine a directory service associated with each of the plurality of assets, obtaining a first sub-asset and a second sub-asset based on the attribute analysis, assigning a backup policy of the plurality of backup policies to each of the two sub-assets, and performing a storage of the FBB based on the backup policies assigned to each of the sub-assets.