Abstract: In various examples, a computing device of a dispersed storage network (DSN) receives a store data request including a data object. The computing device identifies a storage unit pool associated with the store data request. The storage unit pool includes a plurality of storage sets, each of the storage sets associated with a plurality of address ranges that are associated with a respective set of memories of the storage set. The computing device identifies a first set of memories of a first storage set of the storage unit pool, and issues a set of write slice requests to the first set of memories to initiate storage of encoded data slices produced from the data object. When an unfavorable storage condition is detected, the computing device identifies a second set of memories of the first storage set and facilitates storage of the data object in the second set of memories.

Abstract: An illustrative method includes a storage management system detecting an event within a storage system, determining, based on the event, an operation related to a compliance ruleset associated with a compliance policy, and providing a notification of the operation to an orchestration system configured to manage an execution of the operation by a computing system associated with the storage system.

Abstract: Workload planning with quality-of-service (‘QoS’) integration, including: determining, for each of a plurality of entities, one or more QoS thresholds associated with the entity; determining, for each of the plurality of entities, one or more resource utilization levels associated with the entity; and determining, in dependence upon the one or more QoS thresholds associated with the plurality of entities, the one or more resource utilization levels associated with the plurality of entities, and one or more overprovisioning factors associated with the storage system, a risk factor that identifies the likelihood that one or more system resources will be overconsumed by the plurality of entities.

Abstract: A method for execution by one or more computing devices of a storage network includes obtaining status information from a set of distributed storage units that is storing a set of encoded data slices, where the set of distributed storage units includes inactive storage units and active storage units that are rotated between active and inactive in accordance with a rotation scheme. The method further includes activating, based on the status information, a first storage unit of the inactive storage units in accordance with the rotation scheme. The method further includes determining an encoded data slice stored in the first storage unit needs rebuilding and rebuilding the encoded data slice utilizing other encoded data slices of the set of encoded data slices. The method further includes deactivating, based on the status information, a second storage unit of the active storage units in accordance the rotation scheme.

Abstract: A method includes encoding a data segment into a set of encoded data slices using erasure coding; storing, in storage units of a storage network, the set of encoded data slices, in accordance with a shared key-based encryption system (SKBES) having keys shared with the storage units; retrieving, at a periodic rate and in accordance with the SKBES, the set of encoded data slices from the storage units of the storage unit to verify whether individual slices of the set of encoded data slices have been corrupted. When one of the set of encoded data slices stored in one of the storage units has been corrupted, rebuilding the one of the set of encoded data slices by: retrieving the decode threshold number of other slices of the set of encoded data slices, in accordance with the SKBES; reconstructing the one of the set of encoded data slices based on the erasure encoding, to generate a reconstructed data slice; and storing, in accordance with the SKBES, the reconstructed data slice in the one of the storage units.

Abstract: A method of data reduction in a partially encrypted volume includes receiving data to be stored on a storage array, decrypting the data using a first encryption key to generate first decrypted data, and decrypting the data using a second encryption key to generate second decrypted data. The method further includes comparing, by a storage array controller, a first compressibility value of the first decrypted data to a second compressibility value of the second decrypted data. The method further includes storing the first decrypted data if the first compressibility value is greater than or equal to the second compressibility value. The method further includes storing the second decrypted data if the second compressibility value is greater than the first compressibility value.

Abstract: A method of operating a storage system, and related storage system, are provided. The storage system establishes resiliency groups, each having a defined level of redundancy of resources of the storage system. The resiliency groups include at least one compute resources resiliency group and at least one storage resources resiliency group. The storage system supports capability of configurations that have multiples of each of the resiliency groups. Blades of the storage system perform distributed data and metadata storage across modular storage devices, in accordance with the resiliency groups.

Abstract: Intelligent responses to errors in a storage system, including: after a first attempt to read data from a first set of resources in a storage system results in an error, determining whether to issue a second attempt to read data from the first set of resources in a storage system; responsive to determining not to issue the second attempt to read data from the first set of resources in a storage system, retrieving the data from a second set of resources in the storage system; and responsive to determining to issue the second attempt to read data from the first set of resources in a storage system, issuing a second read attempt to read the data, wherein the error correction effort level associated with the second attempt is increased relative to the error correction effort level associated with the first attempt.

Abstract: An illustrative method includes receiving a write request to write payload data to a virtual storage volume; transmitting the write request to a plurality of storage nodes each storing a replica of the virtual storage volume; acknowledging the write request only after a quorum of the storage nodes has stored the payload in their respective kernel memory; and flushing the payloads stored in each kernel memory to persistent storage only after a threshold number of outstanding write requests that have been acknowledged, but not yet flushed, has been reached, the flushing configured to optimize performance for synchronous workloads.

Abstract: A storage network operates by: generating metadata for a data object; first disperse storage error encoding the metadata to produce a set of metadata slices, wherein the first disperse storage error encoding utilizes first dispersal parameters, the first dispersal parameters including a first decode threshold of 1; generating sets of first data slices via a second disperse storage error encoding of data segments associated with the data object, wherein the second disperse storage error encoding utilizes second dispersal parameters, the second dispersal parameters different from the first dispersal parameters and the second dispersal parameters including a second decode threshold greater than 1; producing an additional data segment associated with the data object wherein the additional data segment is different from the data segments and the metadata; and third disperse storage error encoding the additional data segment to produce a set of second data slices, wherein the third disperse storage error encoding u

Abstract: A method for execution by a storage network begins by creating a plurality of vaults in memory addressable by the storage network, where a vault is a virtual memory block associated with a portion of storage network memory, and then determining dispersed storage error encoding parameters for each vault. The method then continues by creating a plurality of vault regions within each vault, wherein a vault region is configured to store a data type of a plurality of data types, where at least one data type of the plurality of data types is associated with a unique access restriction.

Abstract: Systems, methods, and computer readable storage mediums for performing remote replication including receiving, by a target storage system, an indication that a dataset stored on a source storage system will be replicated to the target storage system; identifying, by the target storage system, portions of the dataset that are not already stored on the target storage system; and initiating, by the target storage system, replication of one or more of the portions of the dataset that are not already stored on the target storage system from a source other than the source storage system.

Abstract: A method of operating a storage system having solid-state storage memory with segment level heterogeneity is provided. The method includes mapping data into data segments, and mapping the data segments into data stripes. The method includes writing a first data stripe from a first data segment across a first plurality of blades of the storage system comprising heterogeneous total amounts of the solid-state storage memory per blade, and writing a second data stripe from the first data segment across a second plurality of blades of the storage system.

Abstract: Data associated with storage media utilized by one or more storage systems is received. The data is provided as an input to a machine learning model executed by a processing device. The machine learning model identifies one or more deterministic characteristics from the data. The one or more deterministic characteristics associated with the storage media are received from the machine learning model. A data structure comprising the one or more deterministic characteristics is generated for use in a telemetry process to qualify types of storage media.

Abstract: A method for extending data lifetime for reference in deduplication is provided. The method includes determining that a quantity of user data has at least a threshold amount of data that is re-created in a storage system. The method includes protecting at least portions of the quantity of user data from erasure by garbage collection in the storage system during a predetermined time interval, wherein the protected at least portions are available for data deduplication of further user data in the storage system during the predetermined time interval.

Abstract: Methods and apparatus for asynchronous replication of data in a storage network. In an embodiment, a method begins by a processing module(s) of a computing device identifying at least a first storage set and a second storage set for replicated storage of data. The processing module maintains a synchronization schedule for the first storage set and the second storage set. After initiating storage of a data object in the first storage set, the processing module determines, based at least in part on the synchronization schedule, to synchronize the first storage set and the second storage set. In response to determining to synchronize the first and second storage sets, the processing module determines that the second storage set requires the data object to maintain synchronization with the first storage set, and facilitates storage of the data object in the second storage set.

Abstract: A data distribution server includes a first interface for communicating with a plurality of content providers and a second interface for comminating with a plurality of wireless transceivers. The data distribution server includes memory storing operational instructions and processing circuitry operably coupled to the first and second interfaces and to the memory, where the processing circuitry is configured to execute the operational instructions to receive a portion of a data object from a content provider of the plurality of content providers, generate a plurality of data slices from the portion of the data object, distribute the plurality of data slices between the plurality of wireless transceivers for temporary storage and facilitate transmittal of the plurality of data slices to a user device that is adapted to wirelessly communicate with each wireless transceiver of the plurality of wireless transceivers.

Abstract: Scaling storage resources in a storage volume, including: monitoring a usage of a volume in a storage pool that includes one or more cloud-based storage systems; determining that the usage of the volume exceeds a threshold usage; and based on the determination, expanding the resources that are included in the storage pool for servicing the volume, including: instantiating one or more new virtual drives that are included in the one or more cloud-based storage systems; and adding the one or more new virtual drives to the storage pool.

Abstract: A system with storage memory and a processing device has a logical deletion to physical erasure time bound. The system dereferences data, responsive to a direction to delete the data. The system monitors physical blocks in storage memory for live data and the dereferenced data. The system cooperates garbage collection with monitoring the physical blocks, so that at least a physical block having the dereferenced data is garbage collected and erased within a logical deletion to physical erasure time bound.

Abstract: Generating a transformed dataset for use by a machine learning model in an artificial intelligence infrastructure that includes one or more storage systems and one or more graphical processing unit (‘GPU’) servers, including: storing, within one or more storage systems, a transformed dataset generated by applying one or more transformations to a dataset that are identified based on one or more expected input formats of data received as input data by one or more machine learning models to be executed on one or more servers; and transmitting, from the one or more storage systems to the one or more servers without reapplying the one or more transformations on the dataset, the transformed dataset including data in the one or more expected formats of data to be received as input data by the one or more machine learning models.