Abstract: Various embodiments of the present application set forth a computer-implemented method for accessing data comprising determining a manifest associated with a given user of an application, where the manifest identifies one or more assets that are accessible by the given user, for each of the one or more assets, one of a plurality of endpoint stores that stores data associated with the asset, and for each of the one or more assets, one of the plurality of endpoint stores that stores metadata associated with the asset, generating, based on the manifest, a user namespace that includes a unique reference for each of the one or more assets, and presenting the user namespace to the user.

Abstract: In one embodiment, a data reconciliation engine works with data store nodes included in a distributed data store system to ensure consistency between the data store nodes. In operation, the data reconciliation receives a different data snapshot from each of the data store nodes. In response, the data reconciliation engine generates one or more recommendations designed to resolve inconsistencies between the data snapshots. The data reconciliation engine then transmits each recommendation to a different data store node. Because the data reconciliation engine performs many of the resource-intensive operations included in the data reconciliation process, the resources of the data store nodes may focus primarily on processing client requests instead of performing data reconciliation operations.

Abstract: Various embodiments of the present application set forth a computer-implemented method for accessing data comprising determining a manifest associated with a given user of an application, where the manifest identifies one or more assets that are accessible by the given user, for each of the one or more assets, one of a plurality of endpoint stores that stores data associated with the asset, and for each of the one or more assets, one of the plurality of endpoint stores that stores metadata associated with the asset, generating, based on the manifest, a user namespace that includes a unique reference for each of the one or more assets, and presenting the user namespace to the user.

Abstract: Various embodiments of the present application set forth a computer-implemented method for accessing data comprising receiving, by a first storage controller at a first spoke network and from an entity remote to the first spoke network, a message identifying a first content item, where the first content item is identified based on a task that is to be performed by accessing the first content item, determining, by the first storage controller, a first storage partition that stores the first content item, where the first storage partition is included in a tiered group of storage partitions accessible by the first spoke network, retrieving, by the first storage controller from the first storage partition, the first content item, and causing, by the first storage controller, the first content item to be transmitted to a second spoke network for storage in a second storage partition accessible by the second spoke network.

Abstract: In various embodiments, a node manager configures a “new” node as a replacement for an “unavailable” node that was previously included in a distributed data store. First, the node manager identifies a source node that stores client data that was also stored in the unavailable node. Subsequently, the node manager configures the new node to operate as a slave of the source node and streams the client data from the source node to the new node. Finally, the node manager configures the new node to operate as one of multiple masters nodes in the distributed data store. Advantageously, by configuring the node to implement a hybrid of a master-slave replication scheme and a master-master replication scheme, the node manager enables the distributed data store to process client requests without interruption while automatically restoring the previous level of redundancy provided by the distributed data store.

Abstract: In various embodiments, a node manager configures a “new” node as a replacement for an “unavailable” node that was previously included in a distributed data store. First, the node manager identifies a source node that stores client data that was also stored in the unavailable node. Subsequently, the node manager configures the new node to operate as a slave of the source node and streams the client data from the source node to the new node. Finally, the node manager configures the new node to operate as one of multiple masters nodes in the distributed data store. Advantageously, by configuring the node to implement a hybrid of a master-slave replication scheme and a master-master replication scheme, the node manager enables the distributed data store to process client requests without interruption while automatically restoring the previous level of redundancy provided by the distributed data store.

Abstract: In one embodiment, a data reconciliation engine works with data store nodes included in a distributed data store system to ensure consistency between the data store nodes. In operation, the data reconciliation receives a different data snapshot from each of the data store nodes. In response, the data reconciliation engine generates one or more recommendations designed to resolve inconsistencies between the data snapshots. The data reconciliation engine then transmits each recommendation to a different data store node. Because the data reconciliation engine performs many of the resource-intensive operations included in the data reconciliation process, the resources of the data store nodes may focus primarily on processing client requests instead of performing data reconciliation operations.