Abstract: One example method includes identifying objects that each include one or more segments to be transferred from a source storage tier to a target storage tier, determining a total amount of data to be transferred, using a tiering controller to create worker nodes operable to transfer the segments to the target storage tier, where a number of worker nodes created is based on the amount of data, transferring, from the source storage tier to the target storage tier, only those segments of the objects not already present in the target storage tier, and the transferring of the segments is performed by the worker nodes, and for each of the objects, placing metadata associated with that object in a bucket.

Abstract: One example method includes identifying objects that each include one or more segments to be transferred from a source storage tier to a target storage tier, determining a total amount of data to be transferred, using a tiering controller to create worker nodes operable to transfer the segments to the target storage tier, where a number of worker nodes created is based on the amount of data, transferring, from the source storage tier to the target storage tier, only those segments of the objects not already present in the target storage tier, and the transferring of the segments is performed by the worker nodes, and for each of the objects, placing metadata associated with that object in a bucket.

Abstract: Dynamic rule-based recommendations are disclosed. A rule-base, which includes rules, is received for a data-related operation. Potential targets of the data-related operation are validated against the rule-base. Targets that are eligible or validated using the rule-base may be returned and/or ranked. The data-relation operation may be performed using one of the validated targets.

Abstract: Efficient data transfer is disclosed. A server provides an endpoint for a client. The client can communicate with a cloud storage system through the server rather than connect directly to the cloud storage system. The server is configured to perform requests in a manner that reduces the amount of data transferred to and from the cloud storage system.

Abstract: Systems and methods enabling garbage collection operations and normal system operations concurrently. Concurrent operations are performed by configuring a similarity group to permit garbage collection and normal operations. This may include creating a new subgroup in a similarity group for write and deduplication purposes such that an impacted subgroup can be cleaned.

Abstract: Systems and methods for estimating the number of workers needed to perform a garbage collection operation are disclosed. Similarity groups are used to identify segments associated with objects in a computing system. Using deletion records that identify objects to be deleted, the similarity groups impacted by the deletion records can be identified. The number of workers can be determined based on the impacted similarity groups. More specifically, the number of impacted similarity groups and/or workers can be evaluated in terms of memory requirements, input/output constraints and/or time requirements to estimate the number or workers needed to clean similarity groups impacted by a garbage collection operation.

Abstract: Systems and methods for marking similarity groups impacted by a garbage collection operation are disclosed. Similarity groups are used to identify segments associated with objects in a computing system. Using deletion records that identify objects to be deleted, the similarity groups impacted by the deletion records can be identified. The live segments associated with the impacted similarity groups are also identified. This allows segments that are associated with the deleted objects and that are not associated with any live objects to be removed.

Abstract: One example method includes identifying objects that each include one or more segments to be transferred from a source storage tier to a target storage tier, determining a total amount of data to be transferred, using a tiering controller to create worker nodes operable to transfer the segments to the target storage tier, where a number of worker nodes created is based on the amount of data, transferring, from the source storage tier to the target storage tier, only those segments of the objects not already present in the target storage tier, and the transferring of the segments is performed by the worker nodes, and for each of the objects, placing metadata associated with that object in a bucket.

Abstract: Efficient data transfer is disclosed. A server provides an endpoint for a client. The client can communicate with a cloud storage system through the server rather than connect directly to the cloud storage system. The server is configured to perform requests in a manner that reduces the amount of data transferred to and from the cloud storage system.

Abstract: Efficient data transfer is disclosed. A server provides an endpoint for a client. The client can communicate with a cloud storage system through the server rather than connect directly to the cloud storage system. The server is configured to perform requests in a manner that reduces the amount of data transferred to and from the cloud storage system.

Abstract: Systems and methods for estimating the number of workers needed to perform a garbage collection operation are disclosed. Similarity groups are used to identify segments associated with objects in a computing system. Using deletion records that identify objects to be deleted, the similarity groups impacted by the deletion records can be identified. The number of workers can be determined based on the impacted similarity groups. More specifically, the number of impacted similarity groups and/or workers can be evaluated in terms of memory requirements, input/output constraints and/or time requirements to estimate the number or workers needed to clean similarity groups impacted by a garbage collection operation.

Abstract: Systems and methods for estimating the number of workers needed to perform a garbage collection operation are disclosed. Similarity groups are used to identify segments associated with objects in a computing system. Using deletion records that identify objects to be deleted, the similarity groups impacted by the deletion records can be identified. The number of workers can be determined based on the impacted similarity groups. More specifically, the number of impacted similarity groups and/or workers can be evaluated in terms of memory requirements, input/output constraints and/or time requirements to estimate the number or workers needed to clean similarity groups impacted by a garbage collection operation.

Abstract: Systems and methods for estimating the number of workers needed to perform a garbage collection operation are disclosed. Similarity groups are used to identify segments associated with objects in a computing system. Using deletion records that identify objects to be deleted, the similarity groups impacted by the deletion records can be identified. The number of workers can be determined based on the impacted similarity groups. More specifically, the number of impacted similarity groups and/or workers can be evaluated in terms of memory requirements, input/output constraints and/or time requirements to estimate the number or workers needed to clean similarity groups impacted by a garbage collection operation.

Abstract: Systems and methods enabling garbage collection operations and normal system operations concurrently. Concurrent operations are performed by configuring a similarity group to permit garbage collection and normal operations. This may include creating a new subgroup in a similarity group for write and deduplication purposes such that an impacted subgroup can be cleaned.

Abstract: Systems and methods for marking similarity groups impacted by a garbage collection operation are disclosed. Similarity groups are used to identify segments associated with objects in a computing system. Using deletion records that identify objects to be deleted, the similarity groups impacted by the deletion records can be identified. The live segments associated with the impacted similarity groups are also identified.

Abstract: Systems and methods enabling garbage collection operations and normal system operations concurrently. Concurrent operations are performed by configuring a similarity group to permit garbage collection and normal operations. This may include creating a new subgroup in a similarity group for write and deduplication purposes such that an impacted subgroup can be cleaned.