Snapshot Consolidation for Virtual Machine Storage Efficiency
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Solution Overview
Problem
Virtualization technologies present challenges in managing and recovering data due to higher workload consolidation and the need for instant, granular recovery, especially in virtualized infrastructure environments, where traditional data management methods are inadequate.
Innovation Solution
An integrated data management and storage system that provides a unified primary and secondary storage system with built-in data management, enabling automated storage, backup, deduplication, replication, recovery, and archival of data across physical and virtual computing environments, using a distributed cluster of storage nodes for fault-tolerant data management and near-instantaneous recovery of virtual machines and files.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional data management methods are used in virtualized environments, then data can be stored and managed, but the system cannot provide near-instantaneous recovery and granular access to backup data
Solution Approach 1:
The system segments backup data into snapshots with incremental changes, allowing fast recovery by applying only necessary changes rather than restoring entire systems. The snapshot mechanism divides data into discrete time points, enabling granular recovery at specific moments without requiring complex full system restoration procedures.
Solution Approach 2:
The system performs preliminary actions by continuously capturing incremental changes and maintaining snapshot chains before actual recovery is needed. This preparation allows the recovery process to proceed rapidly by simply selecting a desired snapshot point and applying stored changes, eliminating the need for complex real-time recovery operations.
2Measurement precision
If more snapshots are stored for granular recovery, then recovery precision improves, but storage space requirements increase
Solution Approach 1:
The system extracts only the incremental changes between snapshots rather than storing complete duplicate copies of all data. By taking out only the differences (delta data) and applying them to a base snapshot, the system achieves granular recovery precision while dramatically reducing storage requirements compared to storing full snapshots at every time point.
Solution Approach 2:
Multiple snapshots are merged into a single base snapshot plus incremental change set. Instead of storing separate complete snapshots for each time point, the system combines them into a hierarchical structure where later snapshots build upon earlier ones, reducing total storage while maintaining the ability to recover at any precise moment.
3Productivity
If workload consolidation increases in virtualized infrastructure, then resource efficiency improves, but data management complexity and recovery difficulty increase
Solution Approach 1:
The snapshot and incremental change mechanism serves multiple functions simultaneously: it enables fast recovery, supports granular access to specific time points, allows data consolidation, and maintains compatibility across different virtual machine workloads. This universal approach handles diverse recovery scenarios without requiring separate complex management systems for each use case.
Data Source
AI summary
Methods and systems for reclaiming disk space via consolidation and deletion of expired snapshots are described. The expired snapshots may comprise snapshots of a virtual machine that are no longer required to be stored within a data storage domain (e.g., a cluster of data storage nodes or a cloud-based data store). In some cases, rather than storing an incremental file corresponding with a particular snapshot of the virtual machine, a full image of the particular snapshot may be generated and stored within the data storage domain. The generation of the full image may allow a chain of dependencies supporting the expired snapshots to be broken and for the expired snapshots to be deleted or consolidated. The full image of the particular snapshot may be generated using compute capacity in the cloud or may be generated locally by a storage appliance and uploaded to the data storage domain.