Storage Array Metadata Recovery via Pattern Analysis
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Solution Overview
Problem
Conventional storage systems are unable to recover data from a storage array when its metadata is lost or corrupted, rendering the data unusable without a backup.
Innovation Solution
A system and method for recovering metadata by analyzing the storage array to infer characteristics, such as stripe sizes, piece assignments, RAID levels, and parity information, allowing the configuration database to be restored without a backup, enabling data access and storage operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional storage systems rely on metadata backups for recovery, then data can be recovered when metadata is lost, but the system requires additional backup infrastructure and cannot recover without a backup
Solution Approach 1:
The storage system performs self-diagnosis and self-recovery by automatically analyzing the storage array to infer metadata characteristics without requiring external backup infrastructure. The system uses algorithms to detect stripe sizes, piece assignments, RAID levels, and parity information directly from the stored data patterns
Solution Approach 2:
The patent replaces the mechanical/physical backup infrastructure with computational analysis methods. Instead of relying on physical backup copies of metadata, the system uses computational algorithms to infer and reconstruct metadata from the data patterns existing in the storage array
2Reliability
If metadata is lost or corrupted in conventional storage systems, then the data appears random and unusable, but the system cannot restore logical ordering without backup metadata
Solution Approach 1:
The system converts the harmful situation of lost metadata into a beneficial recovery process by using the existing data patterns in the storage array as the basis for inferring metadata characteristics. The random appearance of data without metadata becomes the very pattern used to reconstruct the metadata
Solution Approach 2:
The patent introduces computational analysis algorithms as an intermediary between the corrupted storage array and the recovery process. These algorithms act as mediators that analyze data patterns and infer metadata characteristics, bridging the gap between lost information and data restoration
3Productivity
If storage arrays use random or pseudo-random data placement, then data can be distributed across multiple devices, but the metadata becomes critical for locating and accessing data
Solution Approach 1:
The system uses feedback from analyzing data patterns in the storage array to iteratively refine metadata inference. By examining the distributed data placement patterns and using this feedback to infer metadata characteristics, the system can reconstruct the logical ordering information needed for data access
Data Source
AI summary
Systems and techniques for recovering a storage array are disclosed. These systems and techniques include determining a size corresponding to a storage stripe of the storage array. Pieces assigned to the storage stripe are identified. A storage configuration corresponding to the pieces assigned to the storage stripe is detected. Ordinal information and parity information are determined corresponding to the pieces assigned to the storage stripe. The size determined corresponding to the storage stripe, identification of the pieces assigned to the storage stripe, the storage configuration, the ordinal information, and the parity information is stored in a data store to reconstruct lost or corrupted metadata corresponding to the storage array.