In-Place Virtual Machine Recovery Using Changed Data Blocks
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Solution Overview
Problem
Existing data recovery systems face high workload latency and data loss during transfer due to the need to restore large volumes of backup data, which can cause significant downtime and disrupt business operations.
Innovation Solution
An in-place data recovery system that identifies and transfers only changed data blocks, preserving the virtual machine's configuration and integrity by restoring data on the same platform, reducing the need for new virtual machine creation and minimizing data transfer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If full snapshot backup data is transferred for data recovery, then data recovery completeness is improved, but workload latency and business downtime increase significantly
Solution Approach 1:
The patent segments the backup data into changed blocks and unchanged blocks. Instead of transferring the complete snapshot, the system identifies and transfers only the changed blocks that need recovery. This segmentation approach maintains recovery completeness for modified data while significantly reducing the volume of data transferred and the associated latency.
Solution Approach 2:
The patent extracts only the necessary changed data blocks from the full snapshot for recovery operations. By using change tracking mechanisms, the system identifies and extracts only the blocks that have changed since the last backup, eliminating the need to transfer and process the entire snapshot data, thus reducing workload latency.
2Reliability
If large volume of backup data is transferred, then data recovery completeness is improved, but business downtime and operational disruption increase
Solution Approach 1:
The backup data is segmented into changed and unchanged portions. The system transfers only the changed segments that require recovery, dramatically reducing the data transfer duration and business downtime while ensuring all necessary data is recovered for completeness.
Solution Approach 2:
The system performs preliminary change tracking and identification before the actual recovery operation. By pre-identifying which blocks have changed since the last backup, the system prepares a targeted recovery list that minimizes data transfer volume and recovery time, thereby reducing business downtime.
3Loss of time
If in-place recovery is implemented, then workload latency is reduced, but data transfer volume decreases
Solution Approach 1:
The patent extracts only the changed data blocks from the full snapshot, transferring minimal data volume to the destination. This extraction approach reduces both the data transfer volume and the time required for recovery operations, effectively addressing both parameters simultaneously.
Solution Approach 2:
The system applies different quality levels to different data blocks - only the changed blocks are transferred and processed, while unchanged blocks are skipped. This local quality approach optimizes both transfer volume and recovery time by focusing resources only where necessary.
Data Source
AI summary
An in-place data recovery method and system include receiving a user request to restore a virtual machine to a version corresponding to a first point in time, identifying a first snapshot of the virtual machine based on the user request, generating a second snapshot of the virtual machine, identifying a second data block in the second snapshot that includes modified data derived from data content of a first data block in the first snapshot, generating reverse incremental backup data including the first data block, and restoring the virtual machine in-place based on the reverse incremental backup data.