Abstract: Techniques are provided for volume group backup, volume group restore, and volume group garbage collection for volume groups backed up to an object store. A volume group workflow is implemented to orchestrate individual consistent volume workflows that are separately and individually implemented by nodes hosting constituent volumes of a volume group. The volume group workflow and the individual consistent volume workflows are performed to back up the volume group to the object store, restore a volume group backup from the object store to a restore destination, and/or perform garbage collection on slots of objects storing data unique to a volume group backup to delete.

Abstract: Techniques are provided for volume group backup, volume group restore, and volume group garbage collection for volume groups backed up to an object store. A volume group workflow is implemented to orchestrate individual consistent volume workflows that are separately and individually implemented by nodes hosting constituent volumes of a volume group. The volume group workflow and the individual consistent volume workflows are performed to back up the volume group to the object store, restore a volume group backup from the object store to a restore destination, and/or perform garbage collection on slots of objects storing data unique to a volume group backup to delete.

Abstract: Techniques are provided for managing objects within an object store. An object is maintained within an object store. The object comprises a plurality of slots. Each slot is used to store a unit of data accessible to applications hosted by remote computing devices. The object comprises an object header used to store metadata for each slot. A determination is made that the object is a fragmented object comprising an in-use slot of in-use data and a freed slot from which data was freed. The object is compacted to retain in-use data and exclude freed data as a rewritten object.

Abstract: Techniques are provided for on-demand creation and/or utilization of containers and/or serverless threads for hosting data connector components. The data connector components can be used to perform integrity checking, anomaly detection, and file system metadata analysis associated with objects stored within an object store. The data connector components may be configured to execute machine learning functionality to perform operations and tasks. The data connector components can perform full scans or incremental scans. The data connector components may be stateless, and thus may be offlined, upgraded, onlined, and/or have tasks transferred between data connector components. Results of operations performed by the data connector components upon base objects may be stored within sibling objects.

Abstract: Techniques are provided for tiering snapshots to archival storage in remote object stores. A restore time metric, indicating that objects comprising snapshot data of snapshots created within a threshold timespan are to be available within a storage tier of a remote object store for performing restore operations, may be identified. A scanner may be executed to evaluate snapshots using the restore time metric to identify a set of candidate snapshots for archival from the storage tier to an archival storage tier of the remote object store. For each candidate snapshot within the set of candidate snapshots, the scanner may evaluate metadata associated with the candidate snapshot to identity one or more objects eligible for archival from the storage tier to the archival storage tier, and may archive the one or more objects from the storage tier to the archival storage tier.

Abstract: Techniques are provided for storing immutable snapshot copes in write once read many (WORM) storage. A snapshot of a volume may be stored into one or more objects formatted according to an object format. An expiry time may be assigned to the snapshot and the one or more objects based upon a creation time of the snapshot and a retention time. The one or more objects may be stored within a remote object store. The one or more objects are retained in an immutable state and cannot be deleted until expiration of the expiry time. In response to identifying an existing object within the remote object store comprising shared snapshot data referenced by the snapshot, an assigned expiry time of the existing object may be modified based upon the expiry time of the snapshot to create a modified expiry time for the existing object.

Abstract: Techniques are provided for incremental snapshot copy to an object store. A list of deallocated block numbers of primary storage of a computing device are identified. Entries for the list of deallocated block numbers are removed from a mapping metafile. A list of changed block numbers corresponding to changes between a current snapshot of the primary storage and a prior copied snapshot copied from the primary storage to the object store is determined. The mapping metafile is evaluated using the list of changed block numbers to identify a deduplicated set of changed block numbers without entries within the mapping metafile. An object, comprising data of the deduplicated set of changed block numbers, is transmitted to the object store for storage as a new copied snapshot.

Abstract: Techniques are provided for implementing a snapshot copy operation between endpoints. One or more snapshots (e.g., snapshots of an on-premise volume) is stored within a source endpoint, such as a source bucket of an object store. A post operation is executed to copy objects comprising snapshot data of a snapshot from the source endpoint to a destination endpoint. A get operation and a tracking object such as a cookie is used to track progress of copying the objects from the source endpoint to the destination endpoint. The tracking object is used to restart the copying of the objects from a point where the copying left off (e.g., in the event there is a failure) without having to restart from the beginning.

Abstract: Techniques are provided for managing objects within an object store. An object is maintained within an object store. The object is used to store data of a snapshot of a file system hosted by a remote computing device. A determination is made that the snapshot was deleted by the remote computing device. Bitmaps describing objects within the object store that are related to snapshots of the file system are evaluated to determine that the object is unique to the deleted snapshot. The object is freed from storage within the object store.

Abstract: Techniques are provided for implementing data requests associated with objects of an object store. A data connector component may be instantiated as a container for processing data requests associated with backup data stored within objects of an object store. The data connector component may evaluate the object store to identify snapshots stored as the backup data within the objects of the object store according to an object format. The data connector component may provide a client device with access to backup data of the snapshots.

Abstract: Techniques are provided for storing immutable snapshot copes in write once read many (WORM) storage. A snapshot of a volume may be stored into one or more objects formatted according to an object format. An expiry time may be assigned to the snapshot and the one or more objects based upon a creation time of the snapshot and a retention time. The one or more objects may be stored within a remote object store. The one or more objects are retained in an immutable state and cannot be deleted until expiration of the expiry time. In response to identifying an existing object within the remote object store comprising shared snapshot data referenced by the snapshot, an assigned expiry time of the existing object may be modified based upon the expiry time of the snapshot to create a modified expiry time for the existing object.

Abstract: Techniques are provided for tiering snapshots to archival storage in remote object stores. A restore time metric, indicating that objects comprising snapshot data of snapshots created within a threshold timespan are to be available within a storage tier of a remote object store for performing restore operations, may be identified. A scanner may be executed to evaluate snapshots using the restore time metric to identify a set of candidate snapshots for archival from the storage tier to an archival storage tier of the remote object store. For each candidate snapshot within the set of candidate snapshots, the scanner may evaluate metadata associated with the candidate snapshot to identity one or more objects eligible for archival from the storage tier to the archival storage tier, and may archive the one or more objects from the storage tier to the archival storage tier.

Abstract: Techniques are provided for storing immutable snapshot copes in write once read many (WORM) storage. A snapshot of a volume may be stored into one or more objects formatted according to an object format. An expiry time may be assigned to the snapshot and the one or more objects based upon a creation time of the snapshot and a retention time. The one or more objects may be stored within a remote object store. The one or more objects are retained in an immutable state and cannot be deleted until expiration of the expiry time. In response to identifying an existing object within the remote object store comprising shared snapshot data referenced by the snapshot, an assigned expiry time of the existing object may be modified based upon the expiry time of the snapshot to create a modified expiry time for the existing object.

Abstract: Techniques are provided for on-demand creation and/or utilization of containers and/or serverless threads for hosting data connector components. The data connector components can be used to perform integrity checking, anomaly detection, and file system metadata analysis associated with objects stored within an object store. The data connector components may be configured to execute machine learning functionality to perform operations and tasks. The data connector components can perform full scans or incremental scans. The data connector components may be stateless, and thus may be offlined, upgraded, onlined, and/or have tasks transferred between data connector components. Results of operations performed by the data connector components upon base objects may be stored within sibling objects.

Abstract: Techniques are provided for on-demand creation and/or utilization of containers and/or serverless threads for hosting data connector components. The data connector components can be used to perform integrity checking, anomaly detection, and file system metadata analysis associated with objects stored within an object store. The data connector components may be configured to execute machine learning functionality to perform operations and tasks. The data connector components can perform full scans or incremental scans. The data connector components may be stateless, and thus may be offlined, upgraded, onlined, and/or have tasks transferred between data connector components. Results of operations performed by the data connector components upon base objects may be stored within sibling objects.

Abstract: Techniques are provided for on-demand creation and/or utilization of containers and/or serverless threads for hosting data connector components. The data connector components can be used to perform integrity checking, anomaly detection, and file system metadata analysis associated with objects stored within an object store. The data connector components may be configured to execute machine learning functionality to perform operations and tasks. The data connector components can perform full scans or incremental scans. The data connector components may be stateless, and thus may be offlined, upgraded, onlined, and/or have tasks transferred between data connector components. Results of operations performed by the data connector components upon base objects may be stored within sibling objects.

Abstract: Techniques are provided for on-demand creation and/or utilization of containers and/or serverless threads for hosting data connector components. The data connector components can be used to perform integrity checking, anomaly detection, and file system metadata analysis associated with objects stored within an object store. The data connector components may be configured to execute machine learning functionality to perform operations and tasks. The data connector components can perform full scans or incremental scans. The data connector components may be stateless, and thus may be offlined, upgraded, onlined, and/or have tasks transferred between data connector components. Results of operations performed by the data connector components upon base objects may be stored within sibling objects.

Abstract: Techniques are provided for implementing data requests associated with objects of an object store. A data connector component may be instantiated as a container for processing data requests associated with backup data stored within objects of an object store. The data connector component may evaluate the object store to identify snapshots stored as the backup data within the objects of the object store according to an object format. The data connector component may provide a client device with access to backup data of the snapshots.

Abstract: Techniques are provided for on-demand creation and/or utilization of containers and/or serverless threads for hosting data connector components. The data connector components can be used to perform integrity checking, anomaly detection, and file system metadata analysis associated with objects stored within an object store. The data connector components may be configured to execute machine learning functionality to perform operations and tasks. The data connector components can perform full scans or incremental scans. The data connector components may be stateless, and thus may be offlined, upgraded, onlined, and/or have tasks transferred between data connector components. Results of operations performed by the data connector components upon base objects may be stored within sibling objects.

Abstract: Techniques are provided for implementing management requests associated with objects of an object store. A data connector component may be instantiated as a container for processing management requests associated with backup data stored within an object store as an object according to an object format. A management request associated with the backup data may be received by the data connector component. A structure associated with the object having the object format may be traversed by the data connector component to identify the backup data. The data connector component may be implemented upon the backup data stored within the object.