A computer-implemented method according to one embodiment includes causing a plurality of I/O queues to be created between an initiator and a storage target device. The created I/O queues are reserved for I/O requests for which adjustments of current priorities of extents of data associated with the I/O requests are to be performed. The method further includes determining identifying information of an I/O request sent from the initiator to the storage target device and determining whether the I/O request was sent from the initiator to the storage target device using one of the created I/O queues. In response to a determination that the I/O request was sent using a first of the created I/O queues having one of the adjustments associated therewith, a tiering manager of the storage target device is instructed to perform the adjustment on the current priority of the extent of data associated with the I/O request.

Methods, systems, and devices for improved data management for memory are described. An apparatus may include a memory array including one or more blocks of memory cells. Data read from a block of memory cells may be written to a buffer, to support providing the data to a host system or modification of the data by the host system. If a quantity of read commands performed at the block of memory cells satisfies a threshold, the data may be written from the buffer to a different block of memory cells, rather than the block from which the data was previously read.

An information processing apparatus selects a magnetic tape as a data migration target from among a plurality of migration-source magnetic tapes based on an index value correlated with a read frequency of valid data recorded in the magnetic tape, the index value being calculated for each of the magnetic tapes, specifies valid data recorded in the selected magnetic tape, and performs control of migrating the valid data to a migration-destination magnetic tape.

Volume migration among a set of storage systems synchronously replicating a dataset for a volume, where volume migration includes: initiating a transfer of the volume in dependence upon determining that a performance metric for accessing the volume stored on a first storage system would improve if transferred to a second storage system; and during the transfer of the volume: determining status information for the transfer; intercepting an I/O operation directed to the volume; and directing, in dependence upon the status information, the I/O operation to either the first storage system or the second storage system.

Systems and methods for performing data protection operations including garbage collection operations and copy forward operations. For deduplicated data stored in a cloud-based storage or in a cloud tier that stores containers containing dead and live segments or dead and live regions such as compression regions, the dead compression regions are deleted by copying the live compression regions into new containers and then deleting the old containers. The copy forward is based on a recipe from a data protection system and is performed using a serverless approach.

A method, apparatus, and system for policy driven data placement and information lifecycle management in a database management system are provided. A user or database application can specify declarative policies that define the movement and transformation of stored database objects. The policies are associated with a database object and may also be inherited. A policy defines, for a database object, an archiving action to be taken, a scope, and a condition before the archiving action is triggered. Archiving actions may include compression, data movement, table clustering, and other actions to place the database object into an appropriate storage tier for a lifecycle phase of the database object. Conditions based on access statistics can be specified at the row level and may use segment or block level heatmaps. Policy evaluation occurs periodically in the background, with actions queued as tasks for a task scheduler.

Data transformation caching in an artificial intelligence infrastructure that includes one or more storage systems and one or more graphical processing unit (‘GPU’) servers, including: identifying, in dependence upon one or more machine learning models to be executed on the GPU servers, one or more transformations to apply to a dataset; generating, in dependence upon the one or more transformations, a transformed dataset; storing, within one or more of the storage systems, the transformed dataset; receiving a plurality of requests to transmit the transformed dataset to one or more of the GPU servers; and responsive to each request, transmitting, from the one or more storage systems to the one or more GPU servers without re-performing the one or more transformations on the dataset, the transformed dataset.

An example method of managing storage for a containerized application executing in a virtualized computing system having a cluster of hosts and a virtualization layer executing thereon, is described. The method includes receiving, at a supervisor container orchestrator, a request for a first persistent volume lifecycle operation from a guest container orchestrator, the supervisor container orchestrator being part of an orchestration control plane integrated with the virtualization layer and configured to manage a guest cluster and virtual machines (VMs), supported by the virtualization layer, in which the guest cluster executes, the guest container orchestrator being part of the guest cluster; and sending, in response to the first persistent volume lifecycle operation, a request for a second persistent volume lifecycle operation from the supervisor container orchestrator to a storage provider of the virtualized computing system to cause the storage provider to perform an operation on a storage volume.

In a storage system such as a SAN, NAS, or storage array that implements hierarchical performance tiers based rated drive access latency, on-drive compression is used on data stored on a first tier and off-drive compression is used on data stored on a second tier. Off-drive compression is more processor intensive and may introduce some data access latency but reduces storage requirements. On-drive compression is performed at or near line speed but generally yields lower size reduction ratios than off-drive compression. On-drive compression may be implemented at a higher performance tier whereas off-drive compression may be implemented at a lower performance tier. Further, space saving realized from on-drive compression may be applied to over-provisioning.

A method for determining a storage location includes one or more processing modules of one or more computing devices of a storage network (SN) receiving a data object to store in a storage network (SN) and determining whether the data object is subject to a legal restriction, where a data object is subject to a legal restriction based on the data object requiring storage in a jurisdiction that subjects the data object to a retention policy. The method continues by determining one or more attributes of a first storage location of a plurality of storage locations and based on a determination that the data object is subject to a legal restriction and at least one attribute of the one or more attributes of the first storage location, transmitting a write threshold number of write requests to a plurality of SUs at the first storage location.