Cloud Snapshot Mounting Without Restoration
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional storage systems face inefficiencies in data replication and management, particularly in handling snapshots and data distribution across multiple storage arrays and cloud services, leading to complexities in data integrity and availability.
Innovation Solution
The implementation of a storage system that utilizes a directed acyclic graph (DAG) of mediums, medium mapping tables, and replication engines to efficiently replicate data across storage arrays and cloud services, enabling deduplication, compression, and encryption while maintaining data integrity and availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is replicated across multiple storage arrays and cloud services using traditional methods, then data availability and integrity are maintained, but network traffic increases and replication efficiency decreases
Solution Approach 1:
The patent extracts only the changed data blocks from the original dataset since the last snapshot, rather than replicating entire datasets. The replication engine identifies and replicates only incremental changes, significantly reducing network traffic while maintaining data availability across storage arrays and cloud services
Solution Approach 2:
The system performs preliminary actions by creating snapshots at designated points in time and maintaining a history of changes. This allows the replication engine to efficiently determine what data has changed and needs replication, avoiding unnecessary network transmission of unchanged data
2Reliability
If traditional snapshot management is used across distributed storage systems, then data integrity is maintained, but system complexity increases
Solution Approach 1:
The patent segments snapshot management into discrete, manageable components including snapshot identifiers, change block tracking, and incremental replication processes. Each snapshot is treated as an independent unit with its own metadata, making the overall system easier to manage and troubleshoot despite the distributed nature of the storage system
Solution Approach 2:
The replication engine acts as an intermediary that manages snapshot creation, tracking, and restoration across distributed storage systems. It handles the complexity of coordinating snapshots between local and remote storage, providing a simplified interface for data integrity management while abstracting away the underlying system complexity
3Loss of energy
If incremental data replication is implemented, then network traffic is reduced, but data consistency across snapshots may be compromised
Solution Approach 1:
The replication engine implements feedback mechanisms to verify data consistency across incremental replications. It tracks change blocks through snapshot identifiers and validates that replicated data maintains proper relationships with parent and child snapshots, ensuring data consistency is preserved even when only incremental changes are transmitted
Solution Approach 2:
The system creates accurate copies of only the changed data blocks while maintaining references to the original snapshot structure. This selective copying approach reduces network traffic while preserving data consistency through maintained relationships between snapshot versions and proper tracking of data block origins
Data Source
AI summary
Leveraging snapshots of remote datasets in the cloud may include: receiving a request to access a snapshot of a dataset, wherein the snapshot is stored in a cloud-based storage system in a cloud computing environment; and mounting the snapshot to an initiator of the request without restoring the snapshot.