Abstract: One example method includes contacting, by a client, a service, receiving a credential from the service, obtaining trust information from a trust broker, comparing the credential with the trust information, and either connecting to the service if the credential and trust information match, or declining to connect to the service if the credential and the trust information do not match. Other than by way of the trust information obtained from the trust broker, the client may have no way to verify whether or not the service can be trusted.

Abstract: Secure credentials (e.g., Diffie Helman (DH) key pairs) may be generated independently of requests to establish communication channels between storage system ports (SSPs) and remote ports, such that secure credentials are pre-generated relative to the requests for which they are utilized to establish secure communication channels. For example, DH key pairs may be pre-generated, and each DH key pair stored in an entry of a DH key table. The number of DH keys to generate and store may be determined based on user input and/or the number of potential communication channels for the storage system. In response to a request to establish a communication channel, an IKE session may be executed, during which a pre-generated DH key pair may be obtained from the DH key table, from which symmetric for secure communication between the SSP and the remote port may be derived.

Abstract: Embodiments of the present disclosure relate to managing communications between slices on a storage device engine. Shared slice memory of a storage device engine is provisioned for use by each slice of the storage device engine. The shared slice memory is a portion of total storage device engine memory. Each slice's access to the shared memory portion is controlled.

Abstract: Described is a system for predictive storage policy selection for a cloud-based storage based on backup monitoring. The system may reduce storage costs incurred by a subscriber of a backup service that leverages a cloud-based storage. The system may monitor backup operations and collect backup statistics associated with the resource requirements of performing a backup to a cloud-based storage. To collect such information, the system may execute a specialized monitoring process that works in conjunction with a backup application and/or server. The collected information may be stored as part of a metadata database associated with the object storage. Accordingly, the system may retrieve the information from the metadata database to predict storage costs associated with performing future backup operations. Based on the predicted storage costs, the system may automatically select an appropriate storage policy.

Abstract: A technique for managing communications between a server and multiple clients includes configuring the server to support multiple sets of certificates for respective clients having respective root certificates. The technique further includes determining an indicator associated with a client root certificate during an initial handshake between a client and the server and providing the client with a server certificate associated with the indicator.

Abstract: Described is a system (and method) for providing multiple types of granular delete operations for a cloud-based object storage. The system may include a server that acts as an intermediary between a client device and an object storage that stores client data. The server may allow a client to perform a hard delete (or permanent) delete and a soft delete. The server may perform a specialized processing to synthetically create the soft delete feature using a permanent object delete operation provided by the object storage. The specialized processing may include manipulating retention periods associated with objects depending on whether the object is subject to a hard delete or a soft delete. As a result, the server may provide the ability for clients to perform a soft delete at an object level using existing storage level APIs that do not directly support such a feature.

Abstract: Data moving micro-services are deployed to a public cloud and a cloud vault target (CVT). A first request is issued to the public cloud for a first snapshot of data belonging to a customer tenant. The first snapshot is accessed to write the data to a first cloud volume in the public cloud. Data of the first cloud volume is vaulted to the CVT via the micro-services. The first cloud volume is maintained in the public cloud. A second request is issued to the public cloud for a second snapshot of the data belonging to the customer tenant. The second snapshot is accessed to write the data to a second cloud volume in the public cloud. Data of the second cloud volume is compared against data of the first cloud volume to identify redundant data. Data of the second cloud volume that is not redundant is vaulted to the CVT.

Abstract: One or more aspects of the present disclosure relate to recovering at least one failed disk. In embodiments, determining a storage reserve capacity allocated for recovering at least one storage device of a storage array is determined. Zero or more storage portions from each storage device of at least one storage cluster for disk recovery are adaptively assigned based on the storage reserve capacity. The failing and/or failed disk using the assigned storage portions is recovered in response to detecting a failing and/or failed disk.

Abstract: Storage management techniques involve determining, if it is determined that lock information associated with a lock operation performed on an object is to be inserted into a storage device, a target digest for representing the lock information; determining whether an idle index not associated with a historical digest exists in an index array for indicating a plurality of storage positions in the storage device; and inserting, if it is determined that an idle index exists in the index array, the lock information into a target storage position in the plurality of storage positions by associating the target digest with the idle index. Accordingly, lock information can be quickly inserted and cleared, thereby improving the system performance.

Abstract: Techniques provide for data deduplication. Such techniques involve: allocating a storage area in a storage device, the storage area including a first storage segment for storing an incompressible data block and a second storage segment for storing a compressed data block, a first size of the first storage segment being greater than a second size of the second storage segment; in response to receiving a write request, determining whether data block to which the write request is related is compressible; in response to determining that the data block is incompressible, adding header information to the data block to generate a first data segment of the first size; and storing the first data segment in the first storage segment through a deduplication operation. Accordingly, such techniques can increase the flexibility and efficiency of data deduplication.

Abstract: Techniques for storage management involve determining, in response to a detection that a disk changes from an unavailable state to an available state, at least one candidate storage unit associated with the disk; acquiring historical access information about the at least one candidate storage unit, the historical information comprising information related to a write request directed to the at least one candidate storage unit when the disk is in the unavailable state; determining a target storage unit from the at least one candidate storage unit based on the historical access information; and rebuilding the target storage unit. Such techniques may, in a low-cost manner, improve rebuilding efficiency and reliability of a storage system.

Abstract: A microservice or serverless process consistency check process comprising locating all the necessary metadata and data objects in the cloud by storing the data objects in the cloud and synchronously mirroring the metadata, which is separately stored in local storage, to the cloud. The process generates a list of data objects in the cloud as “Set A” and the list of metadata objects in the same prefix range as the data objects as “Set B.” The consistency check then verifies whether all objects in Set A are referred to by objects in set B. In the case where there are gaps between the sets, non-existent objects are marked as missing, and unreferenced objects are marked as orphan objects. The list of missing and orphan objects is then sent back to the backup server for analysis and further processing.

Abstract: A memory tier is established in a cluster system having a deduplicated file system. The memory tier includes memory pages configured as huge pages, where writes to the huge pages are exported in a device file that is outside of a user process namespace within which processes of the deduplicated file system run. At least a portion of metadata generated by the deduplicated file system is written to the memory tier. The portion of metadata includes an index of fingerprints corresponding to data segments stored by the deduplicated file system to a storage pool. A determination is made that an instance of the deduplicated file system has failed. A new instance of the deduplicated file system is started to recover file system services by loading the index of fingerprints from the device file.

Abstract: Techniques manage a storage system. Along these lines, a failed storage device is detected among storage devices included in a resource pool of the storage system, and the storage devices belong to a first group and a second group in the resource pool respectively. An extent in the failed storage device assigned for building a stripe in the storage system is determined. A spare reserved extent is selected from respective reserved extents included in respective storage devices among the storage devices based on a mapping relation between the stripe and a plurality of extents in the stripe. The respective reserved extents are shared among the first group and the second group. Data in the extent are rebuilt to the selected spare reserved extent. A reserved storage area can be shared among various storage devices in the resource pool, so as to increase allocatable space in storage devices.

Abstract: Described is a system for automated creation of various data storage environments for application testing. The system may provide an efficient mechanism for creating various computing environments employed by clients of a data protection and recovery service. For example, different clients may utilize different data storage infrastructure (e.g. servers, storage arrays, databases, etc.) on which common backup-related components are overlaid. The system may build different combinations of computing environments and perform application testing across such environments simultaneously (or in parallel) within a virtual environment. Accordingly, the system may verify the operational consistency of backup-related applications across a large sample of client computing environments in an efficient manner.

Abstract: An apparatus in one embodiment comprises at least one processing device comprising a processor coupled to a memory. The at least one processing device is configured to receive in a storage system, from a host device, an identifier of an encryption-enabled logical storage device of the storage system, to utilize the identifier to obtain in the storage system a device-specific key from a key management server external to the storage system, and to utilize the obtained device-specific key to process input-output operations directed to the encryption-enabled logical storage device from the host device. The host device in some embodiments comprises at least one virtual machine and the encryption-enabled logical storage device comprises a virtual storage volume of the at least one virtual machine. Metadata associated with the virtual storage volume illustratively comprises an encryption status indicator specifying whether or not encryption is enabled for the virtual storage volume.

Abstract: One example method includes performing delta operations to protect data. Each delta generated by a data protection operation includes data. The deltas are stored in a delta queue, when moving a current replica to another point in time represented by the selected delta in the delta queue, the deltas are processed so that all relevant data can be applied in a batch. This ensures that when the same extents are represented in multiple deltas, only the oldest version is applied to the replica volume to move the current replica to the selected point in time.

Abstract: Data may be replicated from a host storage system to a target storage system. It may be determined to replicate a first logical storage element on the source storage system to a second logical storage element on the target storage system, wherein the first logical storage element defines a first data portion having a first value. It may be determined that a third logical storage element on the target storage system defines a second data portion having the first value. The first logical storage element may be replicated to the second logical storage element by establishing a deduplication relationship between the second logical storage element and the third logical storage element on the target storage system without transmitting the first data portion from the source storage system to the target storage system.

Abstract: A method of performing write operations that have been received by a data storage apparatus is provided. The method includes (a) storing page descriptors for received write operations within temporary storage, each page descriptor indicating respective data to be written; (b) upon storing each page descriptor, organizing that page descriptor into a shared working-set structure; and (c) operating a plurality of flushers to persist the data indicated by respective page descriptors to long-term persistent storage based on organization of the page descriptors in the shared working-set structure, each flusher accessing page descriptors via the shared working-set structure. An apparatus, system, and computer program product for performing a similar method are also provided.

Abstract: Techniques are provided for estimating a delivery time for a product in a supply chain. One method comprises obtaining an order for at least one product; calculating a similarity-based feature and/or a proximity-based feature for the order; and applying the calculated similarity-based feature and/or the calculated proximity-based feature for the order to a machine learning engine that generates an estimated delivery time for the order, wherein the machine learning engine is trained using characteristics from historical orders. The similarity-based feature for the order can be calculated using a delivery time value of historical orders in a given order cluster where the order was assigned based on a predefined distance metric between the order and features of each order cluster. The proximity-based feature for the order can be calculated using a delivery time value of the historical orders that satisfy one or more predefined recency criteria.