Abstract: Data is replicated on a backup node, where the granularity of the replication can be less than a full volume. A data consistency group comprising a subset of data for a volume is defined for a primary node. A set of differences for the data consistency group is sent to a backup node. The backup node creates change logs in response to receiving the set of differences. In response to receiving a request to access a file having data in the data consistency group, the backup node creates a clone of the file. The backup node determines whether an update to a data block of the file exists in the change logs. In response to determining that the update to the data block exists in the change logs, the backup node updates a copy of the data block for the cloned file with data in the change logs.

Abstract: One or more techniques and/or computing devices are provided for cross-platform replication. For example, a replication relationship may be established between a first storage endpoint and a second storage endpoint, where at least one of the storage endpoints, such as the first storage endpoint, lacks or has incompatible functionality to perform and manage replication because the storage endpoints have different storage platforms that store data differently, use different control operations and interfaces, etc. Accordingly, replication destination workflow, replication source workflow, and/or a proxy representing the first storage endpoint may be implemented at the second storage endpoint comprising the replication functionality.

Abstract: Techniques are provided for performing a resync transfer to recover from a storage site failure. During normal operation of a first site hosting a first volume, data is replicated to a second volume hosted by a second site. If the first site fails, when clients are redirected to the second volume at the second site. When the first site recovers, data modifications made to the second volume are resynced back to the first volume. As part of synchronizing the first volume, a data warehouse is rebuilt at the first site in order to track the location of blocks present on the replication destination. Typically, the data modifications are transferred after the data warehouse is rebuilt, which results in significantly long resync times. The techniques provided herein decrease the resync time by either rebuilding the data warehouse in parallel with resyncing the data modifications or circumvent the need for rebuild.

Abstract: Techniques are provided for performing a resync transfer to recover from a storage site failure. During normal operation of a first site hosting a first volume, data is replicated to a second volume hosted by a second site. If the first site fails, when clients are redirected to the second volume at the second site. When the first site recovers, data modifications made to the second volume are resynced back to the first volume. As part of synchronizing the first volume, a data warehouse is rebuilt at the first site in order to track the location of blocks present on the replication destination. Typically, the data modifications are transferred after the data warehouse is rebuilt, which results in significantly long resync times. The techniques provided herein decrease the resync time by either rebuilding the data warehouse in parallel with resyncing the data modifications or circumvent the need for rebuild.

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 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 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 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.

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 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: One or more techniques and/or computing devices are provided for cross-platform replication. For example, a replication relationship may be established between a first storage endpoint and a second storage endpoint, where at least one of the storage endpoints, such as the first storage endpoint, lacks or has incompatible functionality to perform and manage replication because the storage endpoints have different storage platforms that store data differently, use different control operations and interfaces, etc. Accordingly, replication destination workflow, replication source workflow, and/or a proxy representing the first storage endpoint may be implemented at the second storage endpoint comprising the replication functionality.

Abstract: Data is replicated on a backup node, where the granularity of the replication can be less than a full volume. A data consistency group comprising a subset of data for a volume is defined for a primary node. A set of differences for the data consistency group is sent to a backup node. The backup node creates change logs in response to receiving the set of differences. In response to receiving a request to access a file having data in the data consistency group, the backup node creates a clone of the file. The backup node determines whether an update to a data block of the file exists in the change logs. In response to determining that the update to the data block exists in the change logs, the backup node updates a copy of the data block for the cloned file with data in the change logs.

Abstract: Techniques are provided for managing objects within an object store. An object is maintained within an object store. In an embodiment, a rule is enforced for the object that in-use slots of the object are non-modifiable and unused slots of the object are modifiable. Metadata of additional information for a slot within the object is attached to the object header. A first application allowed to access user data within the slot is provided access to the user data without being provided access to the metadata. A second application allowed access to the user data and the additional information is provided with access to the user data and the metadata for identifying a location of additional information within the object.

Abstract: Techniques are provided for an object file system for an object store. Data, maintained by a computing device, is stored into slots of an object. The data within the slots of the object is represented as a data structure comprising a plurality of nodes comprising cloud block numbers used to identify the object and particular slots of the object. A mapping metafile is maintained to map block numbers used to store the data by the computing device to cloud block numbers of nodes representing portion of the data stored within slots of the object. The object is stored into the object store, and the mapping metafile and the data structure are used to provide access through the object file system to portions of data within the 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 incremental backup to an object store. A request may be received from an application to perform a backup from a volume hosted by a node to a backup target within the object store. A set of changed files within the volume since a prior backup of the volume was performed to the backup target is identified, along with metadata associated with the set of changed files. The metadata is utilized to identify changed data blocks comprising data of the set of changed files that was modified since the prior backup. The changed data blocks are backed up to the object store.

Abstract: One or more techniques and/or computing devices are provided for cross-platform replication. For example, a replication relationship may be established between a first storage endpoint and a second storage endpoint, where at least one of the storage endpoints, such as the first storage endpoint, lacks or has incompatible functionality to perform and manage replication because the storage endpoints have different storage platforms that store data differently, use different control operations and interfaces, etc. Accordingly, replication destination workflow, replication source workflow, and/or a proxy representing the first storage endpoint may be implemented at the second storage endpoint comprising the replication functionality.