Abstract: Maintaining distributed references to data stored on devices of a computer network is described. For instance, a system includes a request component that can communicate a removal request to network equipment to remove a resource from storage by first storage equipment. The system can further include an indicator component that can receive, from the network equipment, a first indication that the removal request did not cause removal of the resource. The removal request can be determined not to have caused the network equipment to remove the resource based on index information of a resource index, which could have identified that the resource was referenced by a resource stub stored on second storage equipment.

Abstract: Maintaining distributed references to data stored on devices of a computer network is described. For instance, a system includes a request component that can communicate a removal request to network equipment to remove a resource from storage by first storage equipment. The system can further include an indicator component that can receive, from the network equipment, a first indication that the removal request did not cause removal of the resource. The removal request can be determined not to have caused the network equipment to remove the resource based on index information of a resource index, which could have identified that the resource was referenced by a resource stub stored on second storage equipment.

Abstract: Modifications made to files (e.g., stub files) within a distributed file storage system over a defined time period are determined. Moreover, the distributed file storage system employs a tiered cloud storage architecture. In one aspect, snapshots of a stub file can be generated at different instances of time. Further, metadata of the stub file within the different snapshots can be compared to determine whether the stub file has been modified. As an example, the metadata can include cache metadata that describes the content within the cache of the stub file and/or mapping metadata that describes the content within cloud storage that is referenced by the stub file.

Abstract: Data sets are synchronized between two or more clusters of nodes that support different versions of files (e.g., stub files) within a distributed file storage system. Moreover, the distributed file storage system employs a tiered cloud storage architecture. In one aspect, for stub files having versions that are not commonly supported by the two or more clusters, an application protocol interface (API) is utilized that employs a deep-copy process wherein cloud-backed data referenced by a stub file is retrieved from a cloud storage (e.g., public cloud) and sent by a primary cluster to one or more secondary clusters. Moreover, the API can determine an optimal synchronization process on a per-file basis.

Abstract: Data storage facilities that provide data storage services frequently perform management tasks (e.g., workflows) on the data files that are being managed. These workflows have a variety of different characteristics and, as such, the data storage facility has an incentive to set different behaviors for different workflows. For example, many types of workflows performing operations on a file, once started, should be executed to completion before another workflow begins performing operations on the file. Thus, a persistent behavior for these workflows is desired such that the workflow can resume to completion after the workflow ceases executing for some reason (e.g., power loss, crash, restart, etc.). However, there is no guarantee that some workflows (e.g., user-initiated workflows) will resume after ceasing execution. For those workflows, a persistent behavior is not desired. A cookie can be employed to provide enhanced management of file workflows such as setting various behavioral parameters.

Abstract: Modifications made to files (e.g., stub files) within a distributed file storage system over a defined time period are determined. Moreover, the distributed file storage system employs a tiered cloud storage architecture. In one aspect, snapshots of a stub file can be generated at different instances of time. Further, metadata of the stub file within the different snapshots can be compared to determine whether the stub file has been modified. As an example, the metadata can include cache metadata that describes the content within the cache of the stub file and/or mapping metadata that describes the content within cloud storage that is referenced by the stub file.

Abstract: Modifications made to files (e.g., stub files) within a distributed file storage system over a defined time period are determined. Moreover, the distributed file storage system employs a tiered cloud storage architecture. In one aspect, snapshots of a stub file can be generated at different instances of time. Further, metadata of the stub file within the different snapshots can be compared to determine whether the stub file has been modified. As an example, the metadata can include cache metadata that describes the content within the cache of the stub file and/or mapping metadata that describes the content within cloud storage that is referenced by the stub file.