Abstract: Techniques are provided for multi-tenant data protection using tenant-based token validation and data encryption. One method comprises obtaining, from a user, a data record to be stored in a multi-tenant storage environment and a token associated with the user. Each data record identifies a tenant associated with the respective data record and the user is authorized to access tenant data of at least one tenant identified in the token. An encryption key of the tenant associated with the data record is obtained and the data record is encrypted using the obtained encryption key and stored. A given data record may be read by obtaining a decryption key of the tenant associated with the given data record and decrypting the given data record using the decryption key. The token may be used to evaluate whether the user is authorized to access the tenant data of the tenant associated with the given data record.

Abstract: Techniques are provided for implementing storage block balancing using volume part migration. One method comprises obtaining a capacity utilization of storage blocks each storing a portion of one or more storage volumes; and when the capacity utilization of a given storage block is above an upper target threshold, migrating a volume part of the given storage block to a different storage block having a capacity utilization below a lower target threshold, wherein the different storage block is within a same storage pool as the given storage block, and wherein the volume part comprises a subset of a storage volume.

Abstract: Source file copying is described. An access object service receives a request to copy a file to a destination and identifies a similarity group identifier for a group of fingerprints corresponding to sequential segments in the file. The access object service communicates a request for the group of fingerprints to a deduplication service associated with a range of similarity group identifiers that include the similarity group identifier. The deduplication service communicates the group of fingerprints, retrieved from fingerprint storage, to the access object service, which communicates the group of fingerprints and the similarity group identifier to the destination.

Abstract: Described is a system (and method) for application-based packing for storing backup data within an object storage. More particularly, the system may efficiently pack backup files into objects having a specialized size by accounting for the source and size of the backup file. For example, the system may determine whether backup files associated with a particular application may be stored within individual objects or packed together within a shared object. Accordingly, by accounting for such criteria the system may perform an intelligent allocation of backup data within a cloud-based object storage. The system may be implemented as part of an incremental backup infrastructure. Accordingly, when allocating the backup files amongst objects, the system may also store specialized metadata to preserve the ability to perform a reconstruction of data (e.g. synthetically) as if a full backup was performed.

Abstract: Described is a system for leveraging incremental backup metadata of a deduplication storage system to perform an efficient data restore. The system may reference metadata stored as part of incremental backup infrastructure to determine only the changes to the data that occurred subsequent to the restore point. As a result, the system may reduce data read processing by retrieving only the changed data from the deduplication storage system. Moreover, the system may reduce the required bandwidth for the restore by providing only the changed data to a target device of the restore. Data retained by the client system such as the current version of the data may then be overwritten with the reduced set of data to complete the restore. As a result, the system may perform an efficient restore by reducing read accesses and bandwidth requirements, and thus, improve overall restore performance.

Abstract: For processing nodes of a cluster of a file server, the IO modules associated with the nodes may be required to be part of a same sub-network. A cluster may be configured to ensure that, for each cluster processing node, at least one other cluster processing node is associated with an IO module on a same sub-network as the IO module associated with the cluster processing node. The user may configure a file server to ensure that a primary node and one or more failover nodes of the file server are on a same sub-network. When configuring IO modules, physical ports having similar or same characteristics may be configured to be on a same sub-network. By doing so, and restricting nodes of a file server to being on a same sub-network, a relatively seamless failover between nodes of a file server may be achieved.

Abstract: Disclosed are techniques for compressing data in a data storage system comprising searching a cluster of nearest neighbors, wherein the cluster has been created using a locality sensitive hashing algorithm, to determine if a data block can be compressed. In alternate embodiments, nearest neighbor clusters can be formed using unsupervised learning. Additionally, nearest neighbors can also be formed in alternate embodiments using one or more of the following algorithms: a k-means clustering algorithm, a k-medoids clustering algorithm, a mean shift algorithm, a generalized method of moment (GMM) algorithm, or a density based spatial clustering of applications with noise (DBSCAN) algorithm.

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

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: 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: 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: 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: 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: 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: 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: 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: 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.