Snapshot Analysis System for Block Device Data Restoration
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Solution Overview
Problem
In computing environments where full backups are infrequent or incremental backups are frequent, the number of backups to maintain and storage space required becomes large, making data restoration and rollback processes time-consuming due to the need to traverse numerous backups sequentially.
Innovation Solution
A snapshot analysis system that analyzes, models, and clusters snapshots of block devices, using a block device emulator to expose only relevant data for operations, reducing the need to retrieve entire block devices and improving data operation efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If incremental backups are performed frequently to maintain data safety, then data protection reliability is improved, but the number of backups increases and storage space required becomes large
Solution Approach 1:
The backup system segments the backup process into full backups and incremental backups. Full backups capture the complete dataset periodically, while incremental backups only capture changes since the last backup. This segmentation allows frequent backups for reliability without proportionally increasing storage requirements, as incremental backups are much smaller than full backups.
Solution Approach 2:
Incremental backups are nested within the backup hierarchy, where each incremental backup depends on and references the previous full or incremental backup. This nested structure allows the system to maintain multiple backup points for reliability while using differential storage, where only changed data blocks are stored in each incremental backup rather than duplicating entire datasets.
2Reliability
If incremental backups are performed frequently to maintain data safety, then data protection reliability is improved, but storage space required becomes large
Solution Approach 1:
The system extracts only the changed portions of data for incremental backups, rather than storing complete copies. By identifying and extracting only the differential data blocks that have changed since the last backup, the system maintains reliability through frequent backups while minimizing the storage space consumed by each incremental backup archive.
Solution Approach 2:
The backup system changes the parameter of backup granularity from full-dataset copies to differential data blocks. By tracking and storing only the parameter of changed data blocks rather than complete datasets, the system enables frequent incremental backups for reliability while keeping total storage requirements manageable through efficient space utilization.
3Reliability
If numerous backups are maintained for data safety, then data protection coverage is improved, but data restoration becomes time-consuming due to sequential traversal requirement
Solution Approach 1:
The system performs preliminary organization of backup data during the backup process itself, creating an indexed structure that records the contents and metadata of each backup point. This preliminary action includes building data structures that map data blocks to their locations in different backups, so that during restoration, the system can directly locate required data without sequentially traversing through numerous backup files.
Solution Approach 2:
The patent introduces an intermediary indexing system that mediates between the stored backups and the restoration process. This intermediary data structure acts as a catalog or map that enables direct access to data across multiple incremental backups, eliminating the need for sequential traversal and significantly reducing restoration time while maintaining comprehensive data protection coverage.
4Reliability
If entire block devices are retrieved for data operations to ensure data completeness, then data integrity is improved, but data operation efficiency decreases
Solution Approach 1:
The system extracts and exposes only the specific data blocks that are relevant to the requested operation, rather than retrieving entire block devices. By identifying and extracting only the necessary data portions based on the operation parameters, the system maintains data integrity for the required data while significantly improving operation efficiency by reducing I/O overhead and processing time.
Solution Approach 2:
The data exposure mechanism applies local quality by providing different levels of data access based on the specific operation requirements. Instead of uniformly exposing entire block devices, the system selectively exposes only the local portions of data that are relevant to each operation, optimizing the balance between data integrity and operational efficiency by matching data exposure to actual needs.
Data Source
AI summary
A snapshot analysis system analyzes a plurality of data snapshots taken in connection with data stored on a block device allocated by a data storage system. The snapshot analysis system may include an ingestor capable of initially detecting new snapshots and adding a root node for the snapshots. The system may include a block device analyzer that analyzes each snapshot to determine its contents, the relationship within data structures extant within the snapshot, and the snapshot's relationship to other snapshots and/or that of other block devices. The system may also include a clustering analyzer capable of determining whether snapshots are associated with multipart block devices, such as LVM or MD RAID devices. The system may further include a block device emulator that exposes data associated with a given snapshot as an addressable block device without necessitating retrieval or exposure of the full block device to which the snapshot is associated.