Abstract: In one aspect, authentication information is received from a first processing device in a second processing device, and a digital signature is generated in the second processing device by signing data that incorporates at least a portion of the received authentication information. The received authentication information is generated at least in part from a secret seed stored in the first processing device. The received authentication information may be combined with the digital signature generated by the second processing device to form a joint signature that is transmitted to an authentication server. In an illustrative embodiment, the received authentication information comprises a tokencode and the digital signature is generated by signing data that incorporates the tokencode. The data that is signed to generate the digital signature may comprise an electronic document having the tokencode appended thereto.

Abstract: One example method includes performing a filtering process that identifies one or more candidate hosts for scheduling of a pod, wherein the candidacy of a host is determined based in part upon an association rule, generating an overall host score for each of the candidate hosts, and scheduling the pod to one of the candidate hosts based on the overall host score of that candidate host. A host risk score and/or pod risk score may be used in the generating of the overall host score.

Abstract: Methods, apparatus, and processor-readable storage media for supporting multiple operations in transaction logging for a cloud enabled file system are provided herein. An example computer-implemented method includes obtaining a plurality of file system operations to be performed on a cloud enabled file system; executing the plurality of file system operations as a single file system transaction; and maintaining a transaction log for the single transaction, the transaction log comprising information for one or more sub-transactions that were completed in conjunction with said executing, wherein the one or more sub-transactions correspond to at least a portion of the plurality of file system operations.

Abstract: One example method includes receiving, at an IO journal, a new entry that identifies a respective disk location L, and data X written at that disk location L, and determining whether a location specified in an oldest entry of the IO journal is specified in any other entries in the IO journal. When the location specified in the oldest entry is not specified in any other entries in the IO journal, adding the new entry to the IO journal, and augmenting the new entry with undo data. Or, when the location specified in the oldest entry is specified in at least one other entry in the IO journal, setting data specified in the oldest entry as undo data for the next entry that identifies that location, and adding the new entry to the IO journal, and deleting the oldest entry from the IO journal.

Abstract: Tiers of compression algorithms may be determined using compression information collected regarding compression ratios achieved for data sets using compression algorithms. Each tier may meet specified criteria regarding expected compression ratios achieved for a specified portion or number of data sets. Compression algorithms of each tier may be implemented by a different hardware device that may include hardware accelerators for the algorithms of the tier. Different tiers, and thus different hardware devices, achieve different levels of compression. A recommendation may be provided using compression information collected, such as from one of the hosts, regarding which hardware device to use for compression. The recommendation may be to purchase a license to use or whether to purchase a particular hardware device for compression. Compression information may be collected by a host that issues tagged I/Os providing a hint regarding what compression algorithm to use for the particular I/O operation data.

Abstract: Techniques described herein relate to a method for deploying workflows.

Abstract: Data retention for a tiered ordered event stream (OES) data storage system is disclosed. Data retention can be applied to demoted data, e.g., data demoted from a first tier to a second tier of data storage devices. The data retention disclosed can avoid demoted events, generally aggregated via a chunk object, file object, etc., from being subject to both a stream-cut operation and a retention period. In embodiments, where a stream-cut instance corresponds to events occurring later in time than a retention end time (RET), all demoted events, e.g., as aggregated by a chunk, file, etc., can be affiliated with the RET. However, where the stream-cut instance corresponds to events occurring earlier in time than the RET, then a portion of the events, e.g., those that will be truncated by performing the stream-cut instance, can be demoted and affiliated with the RET.

Abstract: One example method includes identifying dissimilar items in a data set. A data set may be walked one or more times and the nodes or vertices of the data set may be scored based on the number of times the nodes are touched during the walks. Scores below a threshold score are determined to be dissimilar nodes in the data set. This allows a diverse set of nodes to be identified. A dissimilar data set may be used to prevent unintentional bias in algorithmic training.

Abstract: A method may select a surviving storage node based on environmental conditions. A request for exclusive access to a volume is received. A score based on data associated with an environment of the node is determined for each node in a cluster. Based on the scores, a node to grant exclusive access to the volume is identified, and such exclusive access is granted to the identified node.

Abstract: Techniques described herein relate to a method for managing data protection feature compatibility. The method may include identifying a host data protection feature update event associated with a host; in response to identifying the host data protection feature update event, obtaining host data protection feature information from the host; updating a host data protection feature information repository using the host data protection feature information; updating data protection feature compatibility information using the host data protection feature information and data protection manager data protection feature information; and sending data protection feature compatibility information associated with the host to the host.

Abstract: One example method includes identifying a cloud object as a potential candidate for defragmentation, evaluating the cloud object to determine what portion of segments of the cloud object are expired, when the portion of expired segments meets or exceeds a threshold, segregating the expired segments and unexpired segments of the cloud object, creating a first new cloud object that includes only unexpired segments, creating a second new cloud object that includes only expired segments, and deleting the cloud object from storage.

Abstract: Embodiments of the present disclosure provide a method, an electronic device, and a computer program product for code defect detection. The method described here includes determining log information associated with a defect based on the defect reported during testing of a software product. The method further includes determining a nature of the defect based on the log information. The method further includes determining, based on the nature, the log information, and a memory image file generated when the defect is reported, target code in code of the software product that causes the defect, in response to the nature indicating that the defect is caused by the code of the software product and needs to be repaired. By using the solution of the present application, different analysis strategies for defects may be adopted based on natures of the defects, thereby improving the efficiency of detecting code defects.

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 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: 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: 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: 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: 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: 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 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.