Abstract: A method, system and computer-readable storage medium for transferring data segments from one computer system to a second computing system. Prior to transfer of the data segments, the first system calculates compressibility ratio of each segment and compares the compressibility ratio to a preset threshold. Based on the comparison, the first system assigns a compressibility hint to each segment. The first system transfers the segments to the second system, together with the corresponding compressibility hint. The second system stores each segment in a compressible region or in a non-compressible region based on the hint. Then the second system compresses the compressible region and stores the compressed region in a container, and stores the non-compressible region uncompressed in the container.

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: Systems and methods for synthesizing cloud snapshots of production data. A client system includes data and snapshots may be taken of that data. These snapshots are transferred to the cloud and hydrated to block devices that are similar to the devices on which the production data exists. Snapshots are then taken of the block devices. The cloud snapshots are the same as and correspond to the locally generated snapshots.

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: A method, computer program product, and computing system for determining whether a storage awareness service provider node of a storage system has failed. In response to determining that the storage awareness service provider node has failed, an intermediate storage awareness service may be deployed within the storage system. At least one request may be processed on the storage system via the intermediate storage awareness service.

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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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.