Dynamic Storage Resizing for Bare Metal Restore
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Solution Overview
Problem
Traditional bare metal restore (BMR) operations are limited by the need for a one-to-one correspondence between source and destination storage devices and require manual intervention when destination storage does not match the source in terms of capacity or number, leading to inefficiencies and risks in disaster recovery scenarios.
Innovation Solution
A dynamic data storage management system that analyzes source data storage usage and associates system state information with backup copies, allowing for automatic BMR operations by creating logical volumes on demand and proportionally downsizing destination storage to match source requirements, eliminating the need for manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional BMR requires one-to-one correspondence between source and destination storage devices, then storage configuration matching is simplified, but adaptability to diverse storage environments deteriorates
Solution Approach 1:
The patent creates virtual copies of storage devices through virtualization. Instead of requiring physical one-to-one matching, the system creates virtual storage representations that can be dynamically allocated and mapped to multiple physical destinations, enabling adaptability while managing complexity through abstraction
Solution Approach 2:
The storage management system implements universal interfaces and protocols that allow a single source storage to be restored to multiple different destination types (physical disks, virtual volumes, cloud storage). This multi-functionality enables the same restore process to work across diverse storage environments without requiring environment-specific configurations
2Productivity
If manual intervention is used for storage analysis and reconfiguration in BMR, then restore accuracy is improved, but recovery time deteriorates
Solution Approach 1:
The system implements self-service automation where the storage management software automatically performs storage analysis, capacity calculation, and reconfiguration tasks. The system independently evaluates source storage characteristics, determines optimal destination mappings, and executes reconfiguration without human intervention, achieving both speed and accuracy through automated decision-making algorithms
Solution Approach 2:
The patent incorporates feedback mechanisms where the system continuously monitors storage capacity, performance metrics, and restore progress. This feedback loop allows the automated system to adjust reconfiguration decisions in real-time, ensuring restore accuracy while maintaining rapid recovery speeds through dynamic optimization
3Productivity
If destination storage capacity is reduced below source capacity, then storage resource utilization is improved, but complete restore capability deteriorates
Solution Approach 1:
The patent segments the restore process into multiple phases: critical data identification, priority-based restoration, and incremental recovery. By dividing the restore operation into segments, the system can successfully restore critical business data even when destination capacity is less than source capacity, with non-critical data restored subsequently when additional space becomes available
Solution Approach 2:
The system dynamically changes restore parameters such as data selection criteria, compression ratios, and deduplication levels based on available destination capacity. By adjusting these parameters, the system maximizes the amount of restorable data within constrained storage resources while maintaining complete restore capability for essential business operations
Data Source
AI summary
Illustrative embodiments represent a dynamic on-demand approach to configuring destination storage for bare metal restore (BMR) operations without operator intervention, including destination storage that is smaller than source storage devices. The illustrative operations rely on system state information collected concurrently with or shortly after source data is backed up, thereby capturing current actual storage metrics for the source data. The illustrative embodiments further rely on enhanced data agent components to collect and restore system state information as well as to restore backup data, thereby streamlining the configurations needed for the BMR operation to proceed. Additional business logic matches source mount points with suitable smaller destination storage resources and ensures that the BMR operation successfully completes with diverse and/or smaller storage destinations.