Abstract: Techniques described herein relate to a method for identifying offline accounts for online adoption targeting, including obtaining an account group data set; generating, using the account group data set, an enhanced account group data set comprising the account group data set and a derived data item; obtaining, using a ML model and the enhanced account group data set, a key metric set; performing a clustering analysis using the key metric set and a portion of the enhanced account group data set to obtain account clusters; assigning a weight to a cluster of the account clusters; performing a similarity computation for an offline account of the account group using the key metric set and the portion of the enhanced account group data set to obtain a weighted similarity score; adding the weighted similarity score to a ranked list of weighted similarity scores; and providing the ranked list to an interested entity.

Abstract: Embodiments of the present disclosure relate to a method, an electronic device, and a computer program product for managing a storage device. The method includes: determining, based on the frequency of data access to the storage device, whether a data access component of the storage device will move; determining, if it is determined that the data access component will move, a first storage unit in the storage device based on a storage location of previously accessed data in the storage device, wherein the data access component is located at a first spatial location corresponding to the first storage unit; and sending a read request for data in a second storage unit in the storage device that is adjacent to the first storage unit, so as to cause the data access component to move from the first spatial location to a second spatial location corresponding to the second storage unit. The embodiments of the present disclosure can reduce the latency of data access to the storage device.

Abstract: System extracts backup metadata, comprising system committed change numbers, system change numbers, types, and database version identifiers, for backup copies. System generates data structure, comprising start system change numbers, based on minimums of system committed change numbers, end system change numbers, based on maximums of system change numbers, database version identifiers, and identifiers for archive log backup copies. System identifies dependent system change numbers, based on start system change number to end system change number for backup copy corresponding to database version identifier. System identifies, in data structure, backed-up system change numbers, based on start system change numbers to end system change numbers for archive log backup copies corresponding to database version identifier, which are included in dependent system change numbers.

Abstract: Indices of storage systems are managed. An example method includes: receiving a flush cycle for flushing expired events in a storage system including multiple events in a data stream, determining, based on the flush cycle, a time slice for managing the index of the storage system, creating a slice index node for the time slice in response to determining that the occurrence time of a first event that enters the storage system in the data stream is within the time slice, wherein the slice index node includes an index node of the first event, and adding the slice index node to the index. A corresponding device and a corresponding computer program product are provided. Thus, the index of a large number of events entering the storage system is managed according to the occurrence time of the events, and the storage system can be searched and updated accurately and effectively.

Abstract: Embodiments for handling configuration drift in a data storage system having a plurality of storage nodes. A configuration drift manager system defines a golden configuration dataset for the data storage system, obtains a current configuration dataset of each storage node of the plurality of storage nodes, each of the golden and configuration datasets comprising a plurality of sentences defining a node configuration parameter; determines a distance between each sentence of the golden configuration dataset with each other sentence of the current configuration datasets for each of the plurality of storage nodes; ranks each node based on a distance of its sentences with the golden configuration dataset, and triggers an action on a corresponding node based on its respective ranking.

Abstract: In one embodiment, an apparatus comprises a source system comprising a processing device coupled to memory. The processing device is configured to obtain an IO operation corresponding to an address of the source system. The IO operation comprises first user data. The processing device is further configured to store metadata associated with the IO operation in a first journal barrier of a replication journal of the source system and to close the first journal barrier. The processing device is further configured to determine that the first user data associated with the IO operation is missing from the first journal barrier and to obtain second user data from the address. The processing device is further configured to identify an interval from the first journal barrier to a second journal barrier and to provide the first journal barrier and the interval to a destination system.

Abstract: A method, computer program product, and computing system for receiving a plurality of lock sequences associated with a plurality of objects of the computing device. A plurality of matrices may be generated for each lock sequence of the plurality of lock sequences, thus defining a plurality of lock sequence matrix towers. The plurality of lock sequence matrix towers may be combined, thus defining a combined lock sequence matrix tower. One or more lock sequence conflicts may be identified within the plurality of lock sequences based upon, at least in part, the combined lock sequence matrix tower.

Abstract: The described technology is generally directed towards managing data retention policy for stream data stored in a streaming storage system. When a request to truncate a data stream from a certain position (e.g., from a request-specified stream cut) is received, an evaluation is made to determine whether the requested position is within a data retention period as specified by data retention policy. If any data prior to the stream cut position (corresponding to a stream cut time) is within the data retention period, the truncation request is blocked. Otherwise truncation from the stream cut point is allowed to proceed/is performed. Also described is handling automated (e.g., sized based) stream truncation requests with respect to data retention.

Abstract: A system can receive a file in parts. The system can write a first part to a first temporary file that corresponds to the first part's length at a first location of the first temporary file based on the its part number. The system can for a second part having a same length as the first part, write the second part to the first temporary file at a second location of the first temporary file based on its part number. The system can, in response to receiving a third part that has a different length than the first part, write the third part to a second temporary file at a third location of the second temporary file based on its part number. The system can, after receiving the parts, write data of the second temporary file to an end of the first temporary file, and rename the temporary file.

Abstract: A technique for performing data deduplication operates at sub-block granularity by searching a deduplication database for a match between a candidate sub-block of a candidate block and a target sub-block of a previously-stored target block. When a match is found, the technique identifies a duplicate range shared between the candidate block and the target block and effects persistent storage of the duplicate range by configuring mapping metadata of the candidate block so that it points to the duplicate range in the target block.

Abstract: A technique for performing load balancing between storage nodes includes generating a first performance metric for volumes accessed through a first storage node and generating a second performance metric for volumes accessed through a second storage node. The volumes accessed through the first storage node include a set of volumes that belong to a NAS (network-attached storage) file server hosted by the first storage node. In response to detecting a load imbalance based on the first performance metric and the second performance metric, the technique further includes moving the NAS file server from the first storage node to the second storage node and hosting the set of volumes that belong to the NAS file server from the second storage node.

Abstract: Described is a system for intelligent and reversible data masking of computing environment information shared with an external system. The system may leverage a secure masking agent that acts as an intermediary between a computing system (or environment) and an analytics component. The masking agent may provide real-time reversible data masking that ensures that sensitive information is not exposed outside of a secure (e.g. on-premises) environment, while at the same time ensuring the analytics component receives sufficient contextual information to perform a detailed analysis with the shared information. For example, the system may identify and mask identifying information of a particular server or host, while still retaining certain contextual information such as a network topology.

Abstract: An apparatus comprises at least one processing device. The at least one processing device is configured, for each of a plurality of logical storage devices of a storage system, to determine in a multi-path layer of a layered software stack of a host device a performance level for that logical storage device, to communicate the performance levels for respective ones of the logical storage devices from the multi-path layer of the layered software stack of the host device to at least one additional layer of the software stack above the multi-path layer, and to select particular ones of the logical storage devices for assignment to particular storage roles in the additional layer based at least in part on the communicated performance levels. The additional layer in some embodiments comprises an application layer configured to automatically select a particular one of the logical storage devices for a particular storage role.

Abstract: Embodiments of the present disclosure relate to method, device and computer program product for data backup. The method comprises: in response to receiving from a backup server a data stream to be backed up, dividing the data stream into a plurality of data segments; distributing the plurality of data segments to at least one computing node; in response to receiving an index of a corresponding data segment from a first computing node of the at least one computing node, looking up the index in a global index cache, the index being generated by the first computing node to uniquely identify the data segment, the global index cache storing indexes of data in a backup storage device; in response to the missing index in the global index cache, adding the index into the global index cache; and sending to the first computing node an indication to store the data segment in the backup storage device.

Abstract: A method is provided for use in a storage processor, the method comprising: receiving a write request, the write request including a request to store user data in an array that includes a plurality of solid-state drives (SSD); executing the write request by: identifying metadata that is associated with the write request, and writing the user data and the metadata to different data streams that are opened on the plurality of SSDs; wherein writing the user data and the metadata to different data streams causes: (i) the user data to be stored in one or more first erase units of any of the plurality of SSDs, and (ii) the metadata to be stored in one or more second erase units of any of the plurality of SSDs, such that no part of the metadata is stored on any of the one or more first erase units, and no part of the user data is stored on any of the one or more second erase units.

Abstract: One example method includes deploying an application in a distributed computing environment. Telemetry data is collected that corresponds with the deployment of an application. The telemetry data is received by a machine learning model that was trained with test telemetry data to determine whether the deploying is successful or failed. A successful inference results in continued deployment and a fail inference results in a rollback of the application.

Abstract: Techniques for tracking a lock involve creating an event comprising object information, and extracting the object information in the event through a thread in a thread pool. Such techniques further involve recording lock information comprising the object information according to a determination that the thread executes a lock operation. Such a lock tracking technique for a threading model can record lock information of an object when a thread performs locking and unlocking, and realize tracking of a lock operation and generating a lock analysis report.

Abstract: Methods, apparatus, and processor-readable storage media for automated storage system performance validation are provided herein. An example computer-implemented method includes obtaining user input pertaining to performance testing associated with one or more storage systems deployed in at least one user environment; generating, based at least in part on the obtained user input, a storage system performance test deployment environment comprising at least one controller and at least one data collection mechanism; executing, using the storage system performance test deployment environment, at least one performance test on at least a portion of the one or more storage systems deployed in the at least one user environment; and performing one or more automated actions based at least in part on results from the at least one executed performance test.

Abstract: One example method includes accessing an appearance history of a person, the appearance history including information concerning an appearance of a person at a particular time, generating, based on the appearance history, a forecast that comprises a probability that the person will appear again at some future point in time, determining that the probability meets or exceeds a threshold, and updating a high probability group database to include a facial image of a face of the person.

Abstract: A method for performing a backup operation includes obtaining, by a backup server, a backup request, wherein the backup request specifies a virtual machine to be backed up, wherein the virtual machine is hosted by a production host, and in response to the backup request: obtaining classification data from the backup agent, initiating a backup classification on an unprocessed backup associated with the virtual machine based on the classification data to obtain a sensitivity tag, and initiating a data processing on the unprocessed backup based on the sensitivity tag.