Amazon Technologies, Inc.

Mahmood Miah

Matthew James Eddey

John Sandeep Yuhan

Danny Wei

Abhishek Kumar

Kerry Quintin Lee

Yi Li

Nandakumar Gopalakrishnan

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.

Snapshot clustering techniques for multipart volumes

A system includes a storage volume configured to store a data set in a plurality of data blocks, a data store configured to store a plurality of captures of the data set in a plurality of data chunks, and file retrieval logic. The data set includes a file stored in a first data block of the plurality of data blocks. The file retrieval logic is configured to identify a first data chunk of the plurality of data chunks in which the first data block as captured in a first capture is stored in the data store, retrieve the first data chunk from the data store, and read the first data block as captured in the first capture from the first data chunk.

File extraction out of a backup

A system includes a storage volume configured to store a data set in a plurality of data blocks, a data store configured to store a plurality of captures of the data set in a plurality of data chunks, and file retrieval logic. The data set includes a file stored in a data block of the plurality of data blocks. The plurality of captures includes the file captured at different points in time. The file retrieval logic is configured to identify the plurality of data chunks in which the data block as captured in the plurality of captures is stored in the data store, retrieve the plurality of data chunks from the data store, and read the data block as captured in the plurality of captures from the plurality of data chunks to produce a plurality of file versions.

Version history of files inside a backup

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.

Block device emulation for data snapshots

Data snapshot analysis systems and techniques

Snapshot data operation request processing

Methods and systems for detecting error in data storage entities based at least in part on importance of data stored in the data storage entities. In an embodiment, multiple verification passes may be performed on a data storage entity comprising one or more data blocks. Each data block may be associated with a probability indicating the likelihood that the data block is to be selected for verification. During each verification pass, a subset of the data blocks may be selected based at least in part on the probabilities associated with the data blocks. The probabilities may be adjusted, for example, at the end of a verification pass, based on importance factors such as usage and verification information associated with the data blocks. The probabilities may be updated to facilitate timely detection of important data blocks. Additionally, error mitigation and/or correction routines may be performed in light of detected errors.

Growing community of inventors

Seattle, WA, United States of America

Mahmood Miah