Dynamic Block-Level Backup Triggering via Change Thresholds
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Solution Overview
Problem
Traditional backup operations are scheduled and not sensitive to frequent data changes, leading to increased risk for organizations, as frequently changing data may not be backed up often enough, while rarely changing data is backed up more frequently than necessary, resulting in an overloaded storage manager.
Innovation Solution
A dynamic data storage management approach that monitors data block changes and triggers block-level backups based on specific block-change thresholds, allowing for flexible backup operations and collecting historical data for analysis and predictive purposes, while also enabling reverse lookup operations to identify block-to-file relationships.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional scheduled backup operations are used, then backup operations are simple to implement, but frequently changing data may not be backed up as often as necessary, increasing risk to the organization
Solution Approach 1:
The backup system transitions from static scheduled operations to dynamic event-driven operations. The storage manager continuously monitors data blocks for changes and automatically triggers backup operations when changes are detected, making the backup frequency adaptive to actual data modification patterns rather than following a fixed schedule.
Solution Approach 2:
The system implements continuous monitoring of data block changes and uses this feedback to trigger backup operations. The storage manager receives notifications about modified blocks and responds by initiating appropriate backup actions, creating a closed-loop control system that adapts to changing data states.
2Productivity
If traditional scheduled backup operations are used, then backup operations are easy to manage, but rarely changing data is backed up more frequently than necessary, overloading the storage manager
Solution Approach 1:
The system extracts and monitors only the specific data blocks that have changed, rather than processing entire files or volumes. This selective approach isolates the essential backup trigger events (block changes) from unnecessary backup operations, reducing the storage manager's workload while maintaining data protection for changed data.
Solution Approach 2:
Instead of performing complete file or volume backups, the system performs partial backups of only the specific data blocks that have changed. This partial action approach reduces the amount of data processed and stored, improving efficiency while maintaining adequate protection for modified data.
3Measurement precision
If block-level monitoring is implemented without file identity awareness, then monitoring coverage is comprehensive, but the ability to identify and prioritize specific files for backup is limited
Solution Approach 1:
The system merges block-level monitoring capabilities with file identity awareness by integrating the file system interface. When a block change is detected, the system combines the block change event with corresponding file identity information from the file system, creating a unified view that enables both precise monitoring and intelligent file-level backup decisions.
Data Source
AI summary
A data storage management approach is disclosed that performs backup operations flexibly, based on a dynamic scheme of monitoring block changes occurring in production data. The illustrative system monitors block changes based on certain block-change thresholds and triggers block-level backups of the changed blocks when a threshold is passed. Block changes may be monitored in reference to particular files based on a reverse lookup mechanism. The illustrative system also collects and stores historical information on block changes, which may be used for reporting and predictive analysis.