Abstract: Determining effective space utilization in a storage system, including: identifying an amount of data stored within the storage system that is associated with a user-visible entity; identifying an amount of data stored within the storage system that is associated with all snapshots of the user-visible entity; and reporting, in dependence upon the an amount of data stored within the storage system that is associated with the user-visible entity and the amount of data stored within the storage system that is associated with all snapshots of the user-visible entity, a total capacity utilization associated with the user-visible entity.

Abstract: Sizing resources for a replication target, including: determining an initial resource requirement for a replication source; determining a retention resource requirement for the replication source; and reporting, in dependence on the initial resource requirement and the retention resource requirement, a total resource requirement for replicating the replication source.

Abstract: Using machine learning to dynamically select data reduction techniques, including: generating data describing resource usage in a storage system; determining, by a machine learning model and based on the data, a change to one or more data reduction processes of the storage system; and applying the change to the one or more data reduction processes.

Abstract: Providing Quality of Service (QOS) for replicating datasets including: receiving, by a target data repository from a source data repository, a checkpoint describing one or more updates to one or more datasets stored in the source data repository and the target data repository; adding, by the target data repository, the checkpoint to a first queue for checkpoints directed to one or more volumes in the target data repository, wherein the first queue is included in a plurality of queues for the target data repository; selecting, by the target data repository, one or more queues from the plurality of queues; and servicing an operation from each of the selected one or more queues.

Abstract: Cost optimizing storage management of cloud-based storage systems, including: determining, based on a cost model associated with a cloud computing environment, one or more policies of a cloud-based storage system implemented in the cloud computing environment; and executing, based on the one or more policies, one or more processes in the cloud-based storage system.

Abstract: Determining storage consumption in group of storage resources, including for the group of data units within a group of storage resources: for each data unit in the group of data units, determining whether the data unit is associated with one or more client entities; and for each data unit associated with one or more client entities, determining a category for the data unit; calculating storage consumption for a client based on the category of each data unit; and reporting the calculated storage consumption.

Abstract: Implementing guardrails for non-disruptive migration of workloads between storage arrays, the method comprising: initiating a non-disruptive migration of one or more workloads from a source storage array to a target storage array; validating, prior to completion of the non-disruptive migration, accessibility of the target storage array by one or more hosts; and completing, based on successfully validating the accessibility of the target storage array, the non-disruptive migration.

Abstract: Providing Quality of Service (QoS) for replicating datasets including: receiving, by a target data repository from a source data repository, a checkpoint describing one or more updates to one or more datasets stored in the source data repository and the target data repository; adding, by the target data repository, the checkpoint to a first queue for checkpoints directed to one or more volumes in the target data repository, wherein the first queue is included in a plurality of queues for the target data repository; selecting, by the target data repository, one or more queues from the plurality of queues; and servicing an operation from each of the selected one or more queues.

Abstract: Generating datasets using approximate baselines including receiving, by a source storage system, an instruction to create, on a target storage system, a current snapshot for a source dataset stored on the source storage system, wherein no snapshots for the source dataset exist on the target storage system; selecting, as a baseline dataset, a similar dataset from a plurality of datasets on the source storage system with an existing snapshot on the target storage system, wherein the similar dataset comprises at least a portion of the source dataset; instructing the target storage system to generate a baseline snapshot for the source dataset using a copy of the existing snapshot of the baseline dataset; and transferring, from the source storage system to the target storage system, only a difference between the baseline dataset and the source dataset.

Abstract: Continuous data protection, including sending, to a target data repository from a source data repository, metadata describing one or more updates to one or more datasets stored within the source data repository; generating, based on the metadata describing the one or more updates to the one or more datasets, an ordered log of metadata describing an ordered application of the one or more updates to the one or more datasets; and generating, on the source data repository and based on the ordered log of metadata, the one or more datasets in accordance with the one or more updates corresponding to a specified point in time.

Abstract: Determining effective space utilization in a storage system, including: identifying an amount of data stored within the storage system that is associated with a user-visible entity; identifying an amount of data stored within the storage system that is associated with all snapshots of the user-visible entity; and reporting, in dependence upon the an amount of data stored within the storage system that is associated with the user-visible entity and the amount of data stored within the storage system that is associated with all snapshots of the user-visible entity, a total capacity utilization associated with the user-visible entity.

Abstract: Tracking resource utilization using normalized Input/Output (‘I/O’) operations, including: selecting, for each storage device of one or more storage devices, a corresponding group of input/output (I/O) operations; calculating, for each storage device of the one or more storage devices, a normalized I/O operations per second (IOPS) value based on the corresponding group of I/O operations and a size scalar; and generating a report based on the normalized IOPS value for each storage device of the one or more storage devices.

Abstract: Sizing resources for a replication target, including: determining an initial resource requirement for a replication source; determining a retention resource requirement for the replication source; and reporting, in dependence on the initial resource requirement and the retention resource requirement, a total resource requirement for replicating the replication source.

Abstract: Determining effective space utilization in a storage system, including: identifying an amount of data stored within the storage system that is associated with a user-visible entity; identifying an amount of data stored within the storage system that is associated with all snapshots of the user-visible entity; and reporting, in dependence upon the an amount of data stored within the storage system that is associated with the user-visible entity and the amount of data stored within the storage system that is associated with all snapshots of the user-visible entity, a total capacity utilization associated with the user-visible entity.

Abstract: Generating datasets using approximate baselines including receiving, by a source storage system, an instruction to create, on a target storage system, a current snapshot for a source dataset stored on the source storage system, wherein no snapshots for the source dataset exist on the target storage system; selecting, as a baseline dataset, a similar dataset from a plurality of datasets on the source storage system with an existing snapshot on the target storage system, wherein the similar dataset comprises at least a portion of the source dataset; instructing the target storage system to generate a baseline snapshot for the source dataset using a copy of the existing snapshot of the baseline dataset; and transferring, from the source storage system to the target storage system, only a difference between the baseline dataset and the source dataset.

Abstract: Continuous data protection, including sending, to a target data repository from a source data repository, metadata describing one or more updates to one or more datasets stored within the source data repository; generating, based on the metadata describing the one or more updates to the one or more datasets, an ordered log of metadata describing an ordered application of the one or more updates to the one or more datasets; and generating, on the source data repository and based on the ordered log of metadata, the one or more datasets in accordance with the one or more updates corresponding to a specified point in time.

Abstract: Restoring lost data including detecting that a portion of the dataset stored in a first storage system has become unavailable, obtaining an identifier for the portion of the dataset, locating, using the identifier, a replacement portion of the dataset that is stored at one or more other storage systems, and writing, to the dataset that is stored in the first storage system, the replacement portion of the dataset as a replacement of the portion of the dataset that has become unavailable, where the writing occurs automatically, without user intervention.

Abstract: A uniform model for distinct types of data replication, including receiving, at a source data repository, an update to a dataset; generating, based on the update to the dataset, both metadata describing the update to the dataset and also a metadata representation of the dataset; and initiating, based on the same metadata describing the update to the dataset and also based on the same metadata representation of the dataset, either a first type of data replication or a second type of data replication from among a plurality of types of data replication.

Abstract: Determining storage consumption in group of storage resources, including for the group of data units within a group of storage resources: for each data unit in the group of data units, determining whether the data unit is associated with one or more client entities; and for each data unit associated with one or more client entities, determining a category for the data unit; calculating storage consumption for a client based on the category of each data unit; and reporting the calculated storage consumption.

Abstract: Recovering corrupted data through speculative bitflip and cross-validation, including altering a first data portion stored in a storage device, wherein the first data portion contains an error; calculating a hash value using the altered first data portion; comparing the hash value calculated using the altered first data portion to a stored hash value for the first data portion; and based on the comparing, determining whether the altering corrects the error in the first data portion.