Data Asset Prioritization for Backup Reliability
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Solution Overview
Problem
Current data backup systems treat all data assets equally, failing to prioritize critical assets, which can lead to missed backup windows and dire consequences in real-world deployments.
Innovation Solution
A data asset protection system that allows user or system-defined priority levels based on asset characteristics, such as priority tags, metadata, and grouping, enabling higher priority assets to be elevated in the backup queue and triggering heightened notifications in case of failures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all data assets are treated equally in backup procedures, then the backup system is simple to manage, but critical data assets may miss backup windows and suffer data loss
Solution Approach 1:
The patent applies local quality by assigning different priority levels to different data assets based on their characteristics. Each asset can have its own priority tag (high, medium, low) that determines its treatment in the backup queue. This allows critical assets to receive enhanced protection while non-critical assets follow standard procedures, resolving the contradiction between reliability and complexity.
Solution Approach 2:
The system changes the parameter of asset priority from a uniform state to a variable state with multiple priority levels. By introducing priority tags and allowing dynamic priority assignment, the system can adjust backup behavior based on asset importance, thereby improving reliability without requiring complete system redesign.
2Productivity
If priority levels are assigned to data assets, then critical assets can be elevated in backup queue, but the backup system becomes more complex to manage
Solution Approach 1:
The system implements self-service by allowing assets to automatically receive appropriate priority treatment based on their assigned characteristics and tags. Once priorities are configured, the backup system autonomously manages the queue ordering and execution without requiring continuous manual intervention, thereby maintaining ease of operation while improving productivity.
Solution Approach 2:
Priority levels and tags are assigned to assets in advance during configuration or metadata generation. This preliminary action ensures that when backup operations occur, the system already has the information needed to efficiently order the queue, eliminating the need for complex real-time decision-making and maintaining operational simplicity.
3Reliability
If higher priority assets are elevated in backup queue, then critical data is protected first, but the backup queue management becomes more complex
Solution Approach 1:
The queue management system applies local quality by treating individual assets differently based on their priority tags. High-priority assets are elevated in the queue while low-priority assets remain in standard positions. This localized differentiation ensures data integrity for critical assets without requiring complete reorganization of the entire queue management system.
Data Source
AI summary
Embodiments for a data protection method of prioritizing data assets for backup operations. A base priority of data assets operated on by the backup system is first determined as defined by certain characteristics, along a defined scale. The process then prioritizes certain data assets using priority tagging, grouping factors, and metadata modifiers to generate an interim net priority. If any assets have the same prioritization value, other asset attributes are used to further prioritize any tied assets. The process then performs a priority response action, such as notifying the user (normally or urgently) based on the asset prioritization. The backup/restore operations are then performed on the data assets in an order based on the final prioritization values.