Key-Value Database Indexing for Virtual Backup Efficiency
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Solution Overview
Problem
Protecting data in virtualized computing environments is inefficient due to the time and resources required for conventional backup methods, especially as the amount of data increases.
Innovation Solution
Implementing a deduplicated data repository and virtual environment manager to take snapshots of virtual machines, allowing for efficient incremental backups by tracking changed blocks and using key-value databases to index and recover individual files without mounting entire virtual disk images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional backup methods are used to protect data in virtualized computing environments, then data protection is achieved, but considerable time and resources are required to complete the backup
Solution Approach 1:
The virtual disk image is segmented into individual files and folders, allowing the backup system to process and protect only the changed portions rather than the entire disk image. This segmentation enables incremental backups that reduce time and resources while maintaining comprehensive data protection.
Solution Approach 2:
The system performs preliminary actions by scanning and indexing the virtual disk image before backup to identify changed blocks and files. This preliminary analysis enables the backup system to target only the necessary data for protection, significantly reducing backup time and resource consumption.
2Reliability
If conventional backup methods are used to protect data in virtualized computing environments, then data protection is achieved, but considerable resources are required to complete the backup
Solution Approach 1:
The system extracts only the changed blocks and files from the virtual disk image for backup processing. By taking out only the necessary portions rather than the entire image, the system reduces resource consumption while maintaining effective data protection for modified data.
Solution Approach 2:
The backup process segments the virtual disk into individual files and folders, allowing selective processing of changed portions. This segmentation reduces the quantity of data that needs to be processed and stored, thereby reducing backup resources required.
3Loss of information
If the entire virtual disk image is mounted for recovery, then complete data access is achieved, but time is consumed for recovery operations
Solution Approach 1:
The system extracts and indexes metadata about files and folders within the virtual disk image, enabling users to search for and recover specific files without mounting the entire disk image. This extraction of essential information allows fast recovery of individual files while maintaining complete data accessibility.
Solution Approach 2:
The system performs preliminary indexing and scanning of the virtual disk image to create a searchable database of files and their locations. This preliminary action enables rapid file recovery operations without requiring time-consuming mounting and scanning of the entire disk image during recovery.
4Productivity
If incremental backups tracking changed blocks are implemented, then backup efficiency is improved, but system complexity increases
Solution Approach 1:
The system introduces an intermediary indexing mechanism that tracks changed blocks and files between backups. This intermediary structure simplifies the backup process by providing a clear record of changes, making the incremental backup approach more manageable despite the added complexity of tracking mechanisms.
Data Source
AI summary
Files from a master file table are identified. A key/value database based on the identified files is generated where the key includes directory information and the value includes file metadata. The key/value database is stored in a storage device. Identifying files from a master file table includes parsing a VMDK to isolate a master file table region.