Granular Exchange Data Restore via Virtual File System
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Solution Overview
Problem
Collaborative software applications like Microsoft Exchange Server face downtime and resource inefficiency during data restoration due to time-consuming image-based full-restores, which compromise user availability and require extensive resources.
Innovation Solution
Implementing a granular-level restore process using a virtual file system like AxionFS, which allows selective restoration of specific data items, reducing downtime and resource usage by exposing backup data as a local file system for efficient data retrieval and management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If image-based full restore is performed, then data recovery is achieved, but application availability is compromised and downtime increases
Solution Approach 1:
The patent segments the backup data into individual item-level units (emails, calendars, contacts) rather than restoring the entire database image. This allows selective restoration of only the lost or corrupted items, significantly reducing the time required and maintaining application availability during the restore process.
Solution Approach 2:
The patent extracts specific data items from the backup storage and restores only those items that are lost or corrupted, rather than extracting and restoring the entire backup image. This extraction approach minimizes the restore time and reduces downtime while still achieving complete data recovery.
2Reliability
If image-based full restore is performed, then data recovery is achieved, but system resources are consumed excessively
Solution Approach 1:
The patent divides the restoration process into individual item-level operations, allowing the system to process and restore only the necessary data items rather than the entire database. This segmentation reduces CPU usage, memory consumption, and I/O operations, thereby lowering overall resource consumption during recovery.
Solution Approach 2:
The patent extracts and restores only the specific data items that are lost or corrupted, avoiding the need to process and restore the entire backup image. This extraction approach significantly reduces the computational and I/O resources required during the restoration process.
3Reliability
If image-based full restore is performed, then complete data recovery is achieved, but operational efficiency is reduced
Solution Approach 1:
The patent implements segmentation at the item level, allowing administrators to restore only specific lost or corrupted items rather than the entire database. This approach maintains operational efficiency by minimizing the time the system is occupied with restoration operations and reducing the impact on normal business operations.
Solution Approach 2:
The patent applies partial restoration by restoring only the necessary data items rather than the entire backup image. This partial action approach improves operational efficiency by reducing the time and resources required for recovery while still achieving complete data recovery for the affected items.
Data Source
AI summary
A method for restoring associated with a collaborative software application is disclosed. A virtual file system exposing backup data of a collaborative software application stored in a backup data storage is created. A selection of a portion of the backup data to be restored to the collaborative software application is received via an interface associated with the virtual file system. The selected portion of the backup data is caused to be granularly restored to the collaborative management system without restoring one or more unselected portions of the backup data. A write capability of the virtual file system is used to modify a portion of the restored data in response to a write operation by the collaborative software application.