A data management method includes receiving, by a management server, a first request, determining, based on an identifier of a first user in the first request, whether a shadow tenant bucket associated with the identifier of the first user exists, and if the shadow tenant bucket associated with the identifier of the first user exists, storing, in the shadow tenant bucket associated with the identifier of the first user, an acceleration engine image (AEI) that the first user requests to register, where a shadow tenant bucket is used to store an AEI of a specified user, and each shadow tenant bucket is in a one-to-one correspondence with a user.

Technology described herein can be employed to automatically recommend a tiering policy for data storage of data at a data storage system, such as a cloud storage system. An example method can comprise determining, by a system comprising a processor, context information defining a data storage attribute applicable to data at a cloud storage system. The method can comprise, in response to determining the context information, generating, by the system, a tiering policy defining an element of tiering storage of data at the cloud storage system, wherein the tiering policy is based on the data storage attribute defined by the context information. The method also can comprise, in response to generating the tiering policy, outputting, by the system, the tiering policy to a storage device associated with a customer. The analysis can be performed using an artificial intelligence process, machine learning process or a combination thereof.

A semiconductor memory device is provided. The semiconductor memory device includes a memory core including a plurality of memory cells configured to store a plurality of data received from an external processor; and a statistical feature extractor disposed on a data path between the external processor and the memory core, the statistical feature extractor being configured to analyze statistical characteristics of the plurality of data, identify at least one statistical feature value associated with the statistical characteristics, store the at least one statistical feature value and transmit the at least one statistical feature value to the external processor.

Techniques described herein relate to systems and methods of data storage, and more particularly to providing layering of file system functionality on an object interface. In certain embodiments, file system functionality may be layered on cloud object interfaces to provide cloud-based storage while allowing for functionality expected from a legacy applications. For instance, POSIX interfaces and semantics may be layered on cloud-based storage, while providing access to data in a manner consistent with file-based access with data organization in name hierarchies. Various embodiments also may provide for memory mapping of data so that memory map changes are reflected in persistent storage while ensuring consistency between memory map changes and writes. For example, by transforming a ZFS file system disk-based storage into ZFS cloud-based storage, the ZFS file system gains the elastic nature of cloud storage.

The described technology is generally directed towards managing accounts for connecting applications to (e.g., third party) cloud storage providers. Various types of cloud storage providers and different accounts, e.g. corresponding to different usage scenarios with properties such as regions, storage tier levels, costs and so forth, are available to user applications. In one implementation, a user application provides desired account properties to a cloud credential manager via a REST API call to obtain the account information for an account, including credentials, configuration data and the like, returned in in a REST API response. The described technology facilitates selection of an account by the cloud credential manager based on matching the specified properties. Load balancing and storage costs can also be factors in the selection, and random selection is also available.

One example method includes receiving a group of files, two or more of the files being of different respective file types, creating a backup saveset that includes the group of files, classifying each of the files in the backup saveset based in part on the respective file types of the files, assigning a respective storage media type to each of the classified files in the backup saveset, and transmitting the backup saveset to a storage site.

Methods, apparatus, and processor-readable storage media for automatically processing storage system data and generating visualizations representing differential data comparisons are provided herein. An example computer-implemented method includes obtaining current data from a first storage system and historical data from the first storage system and/or one or more additional storage systems; determining, for the first storage system, at least one current state value for at least one storage system parameter by processing the current data using a first hashing algorithm; determining, for the first storage system with respect to the first storage system and/or the additional storage systems, at least one differential state value for the at least one storage system parameter by processing the current data and the historical data using a second hashing algorithm; and generating data visualizations based on the current state value(s) and/or the differential state value(s).

A method for dynamic access control in a virtual storage environment is provided. Embodiments include providing, by a component within a cluster of virtual computing instances (VCIs), one or more computing node identifiers associated with the cluster to a management entity associated with a file volume. Embodiments include modifying, by the management entity, an access control list associated with the file volume based on the one or more computing node identifiers. Embodiments include determining, by the component, a configuration change related to the cluster. Embodiments include providing, by the component, based on the configuration change, an updated one or more computing node identifiers associated with the cluster to the management entity. Embodiments include modifying, by the management entity, the access control list associated with the file volume based on the updated one or more computing node identifiers.

Techniques for provisioning storage may include: initially provisioning storage for a storage group of logical devices; tagging the storage group to enable autonomous storage provisioning; receiving a plurality of parameters used in connection with performing autonomous storage provisioning for the storage group, wherein the plurality of parameters includes a first parameter denoting a threshold amount of consumed storage of the storage group, a second parameter denoting a storage capacity expansion amount by which to expand the storage capacity of the storage group, and a third parameter denoting a system-wide threshold of consumed backend non-volatile storage; determining, in accordance with the plurality of parameters, whether to expand a current storage capacity of the storage group; and responsive to determining to expand the current storage capacity of the storage group, performing first processing to automatically expand the current storage capacity of the storage group in accordance with the second parameter.

The invention concerns a storage method for storing, on data servers (3, 4), data file (5, 61 to 64) slices (51 to 58) from the execution of a plurality of processes (65 to 68) of one or more applications (83, 85), comprising: distributing the stored data file (5, 61 to 64) slices (51 to 58) over different data servers (3, 4), characterized in that: this distribution is carried out in such a way that the data file (5, 61 to 64) slices (51 to 58) likely to be subsequently accessed simultaneously by different application (83, 85) processes (65 to 68) are stored on different data servers (3, 4) so as to reduce the subsequent access, to each of all or part of these data servers (3, 4) by too many application (83, 85) processes (65 to 68) simultaneously, and in that: the determination of the data file (5, 61 to 64) slices (51 to 58) likely to be subsequently accessed simultaneously by different application (83, 85) processes (65 to 68) has been carried out, during a prior phase of executing these application (83, 85) processes (65 to 68), by observing the behavior of these application (83, 85) processes (65 to 68) in order to access these stored data file (5, 61 to 64) slices (51 to 58) over time.