Backup Recovery for Deleted Virtual Checkpoints
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Solution Overview
Problem
In virtual environments, changes such as checkpoint deletions in the disk chain often result in unnecessary full backups, leading to inefficiencies in data protection operations due to mismatches between the host and backup server configurations, increasing bandwidth and resource usage.
Innovation Solution
The system identifies and saves metadata related to deleted checkpoints and their parent-child relationships, allowing for the merging of data during backup operations, which enables the use of existing backups and reduces the need for full data transfer by only transferring new data during recovery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a full backup is performed whenever the virtual disk chain changes, then the backup data consistency is maintained, but the backup time and resource consumption increase significantly
Solution Approach 1:
The patent applies partial action by performing only incremental backup operations instead of full backups. The system identifies that checkpoint deletions are structural changes rather than data changes, so it performs partial backups that only capture actual data modifications, excluding structural metadata changes. This resolves the contradiction by maintaining backup consistency through selective partial backups rather than complete full backups, significantly reducing backup time while preserving data integrity.
Solution Approach 2:
The patent changes the parameter of backup operation type from always-full to conditional (full vs. incremental). The system monitors the type of changes in the virtual disk chain and adjusts the backup strategy accordingly - performing full backups only when necessary and incremental backups when changes are minor or structural. This dynamic parameter adjustment maintains reliability while optimizing backup time based on actual change characteristics.
2Reliability
If a full backup is performed whenever the virtual disk chain changes, then the backup completeness is ensured, but the bandwidth and processing resources are wasted
Solution Approach 1:
The system performs partial backups that capture only the necessary data changes rather than complete full backups. By analyzing the type of changes in the virtual disk chain, the system identifies structural changes (checkpoint deletions) versus actual data changes, and performs backups only for the latter. This ensures backup completeness for actual data modifications while avoiding waste of bandwidth and processing resources on structural metadata changes.
Solution Approach 2:
The patent extracts and separates structural changes from data changes in the virtual disk chain. The system identifies checkpoint deletions as structural metadata changes and excludes them from backup operations, extracting only the essential data changes that require backup. This extraction approach maintains backup completeness for meaningful data while eliminating unnecessary bandwidth and processing resource consumption associated with backing up structural metadata.
3Measurement precision
If the system treats any virtual disk chain change as a mismatch, then the backup accuracy is maintained, but the operational efficiency decreases
Solution Approach 1:
The patent applies local quality by differentiating between types of changes in the virtual disk chain and applying different backup strategies to different locations in the change set. Structural changes (checkpoint deletions) are treated differently from data changes (file modifications). The system performs local analysis of each change type and applies appropriate backup actions, maintaining backup accuracy for data changes while improving operational efficiency by excluding structural changes from full backup triggers.
Solution Approach 2:
The system changes the parameter of change detection from binary (any change = full backup) to multi-category (structural change vs. data change). By introducing this parameter differentiation, the system maintains backup accuracy for actual data modifications while improving operational efficiency by avoiding unnecessary full backups triggered by structural metadata changes. This parameter refinement allows selective backup triggering based on change significance.
Data Source
AI summary
Backup operations may save a full backup and subsequent checkpoints. Systems and methods for handling backup and restore operations when checkpoints are deleted. Checkpoints can be merged during a restore operation to account for deleted checkpoints. Also, the backup can continue to leverage existing backups even though checkpoints have been deleted.