Abstract: The present disclosure provides approaches for scalable leadership election using a zero-compute witness in a multi-processing computing environment. As provided herein, a zero-compute witness serves to provide for witness functionality without requiring a running witness process at a remote location. In some embodiments, the zero-compute witness is implemented as a data structure stored on cloud storage (e.g., as a cloud storage object) and is writable using conditional write commands such as HTTP conditional writes or compare-and-swap commands (CAS). In some embodiments, the zero-compute witness is initially configured as an empty data structure that is accessible by multiple nodes in the multi-process computing environment.

Abstract: A bypassing technique bypasses an indexing service and provides a bypass data path for transferring/retrieving snapshots from a production cluster to an object store. In an embodiment, the production cluster may determine how extents of the snapshots are packed into objects of the object store and transfers the snapshots directly to the object store over the bypass data path. Once the snapshot transfer is completed, the production cluster provides location metadata as to how the snapshot extents are packed into objects to the indexing service. The indexing service is invoked to create an index of the location metadata and is not involved in the data transfer of the snapshots. In another embodiment, the production cluster identifies a snapshot to restore and queries the indexing service to compute the deltas between the snapshot to be restored and a reference snapshot. The indexing service returns a set of segments that indicates the changed delta regions between the two snapshots.

Abstract: Systems and methods for scalable tracking of objects to be replicated are disclosed. A method may include in a first time period, updating, by one or more processors, a data structure with metadata of a received object to be replicated, wherein the data structure includes a plurality of classifications of objects to be replicated based on when the objects were received, in a second time period, after the first time period, updating, by the one or more processors, the data structure to modify a classification of the object based on the object being received in the first time period, and replicating, by the one or more processors, the object based on the modified classification of the object.

Abstract: Methods, systems, and computer program products for multi-cloud shared data management. A first storage facility on a first cloud is established and a second storage facility on a second cloud established. The first cloud and the second cloud comprise at least respective first deduplication metadata and second deduplication metadata. In response to receipt of a request to store a content object comprising at least one candidate deduplication chunk, an inter-cloud deduplication protocol is initiated. The inter-cloud deduplication protocol determines whether or not a candidate deduplication chunk of a data item is already stored at either the first cloud or the second cloud. In the event that the candidate deduplication chunk of the data item deemed to have been already stored then, rather than storing a further copy of the bit sequence corresponding to the candidate deduplication chunk, instead, merely referring to the location of the already stored candidate deduplication chunk.

Abstract: A system may include a memory having computer-readable instructions stored thereon and a processor that executes the computer-readable instructions to receive, from a user, a first login credential associated with an organization on a database management service. The system may receive, from the user, a selection of the first cloud account, retrieve a second login credential for the first cloud account based on the selection, automatically log in to the first cloud account using the second login credential, receive, from the user, input to perform an operation on data in the first database on the first cloud, and transmit, to the first cloud, using the second login credential for the first cloud account, a signal to perform the operation based on the input.

Abstract: Techniques for authenticating user access to a resource and providing access to the resource include non-transitory computer-readable media storing program instructions that, when executed by one or more processors associated with a first computing device, cause the one or more processors to perform a method including receiving, from a client device, a first request for an authentication token to access a resource and identifying a second computing device through which the resource is accessible. The method further includes transmitting a second request to the second computing device for the authentication token, receiving a signed authentication token from the second computing device, wherein the authentication token is signed by the second computing device and specific to the client device, and providing the signed authentication token to the client device.

Abstract: Techniques for pre-processing metadata for faster background decisions include, in response to a metadata entry associated with storage of data in a cluster being modified, generating a summary entry corresponding to the metadata entry. The summary entry includes a subset of the information from the metadata entry. A data management action is performed based upon a scanning process that reads a plurality of summary entries corresponding to a plurality of metadata entries for data in the cluster.

Abstract: In some embodiments, a method for tuning a disaster recovery preparation system for a storage system includes determining whether the disaster recovery preparation system has not met a recovery point objective; and in response to determining that the recovery point objective is not met: determining a state of the storage system; applying a machine learning model to determine a change to one or more of a plurality of adjustable parameters of the disaster recovery preparation system based on the state of the storage system and the recovery point objective that is not met; adjusting the one or more of the plurality of adjustable parameters based on the determined change to the one or more parameters; after adjusting the one or more parameters, monitoring one or more metrics of the disaster recovery preparation system or the storage system; and updating the machine learning model based on the monitoring.

Abstract: A database management system receives a user request for provisioning a database, autonomously selects a datacenter for provisioning the database based at least on a first pre-defined rule, autonomously selects at least one cluster in the datacenter based at least on a second pre-defined rule, determines a network location of each of the at least one cluster, and provisions the database on each of the at least one cluster using the network location of each of the at least one cluster.

Abstract: An improved flushing technique controls a draining speed of data from a temporary storage tier to a backend storage tier of a node so that draining logic does not overwhelm an input/output (I/O) workload that is serviced by the storage tiers. Illustratively, the temporary storage tier is a persistent write buffer embodied as an operations log (oplog) and the backend storage tier is persistent physical disk storage embodied as an extent store. The technique improves an oplog flushing algorithm by enabling control of the oplog draining speed (rate) to provide consistent performance when the I/O workload (e.g., a primary ingest I/O stream) is serviced by the extent store and/or oplog during one or more states (e.g., static inertia state, idle state and rebuild state) of the oplog.

Abstract: Placement scenario optimization mechanisms for automatic placement of computing entities onto nodes of a running multi-node computing cluster. A set of failure mode parameters define a high-availability requirement of the multi-node computing cluster. In advance of a failure event, and responsive to a determination that a then-current computing entity placement does not satisfy the high-availability requirement, the cluster is analyzed and a plurality of feasible placement scenarios are generated. Optimization criteria are applied to the feasible placement scenarios such that a best choice from among the feasible placement scenarios is identified and applied to the virtual machine placements over the cluster. A change monitoring and detection facility continually observes the multi-node computing cluster to detect a change of a failure mode parameter or to detect a change to the configuration of the virtual machines.

Abstract: Methods, systems, and computer program products for thwarting a malware attack. A data storage system stores data items, some of which data items correspond to snapshots. Upon identification of a possible ransomware attack on a data item, the system identifies a version of the snapshot that is not subject to the ransomware attack and seeks to protect the data state of the system from further damage (e.g., due to performance of unauthorized operations on the version of the snapshot that is not subject to the ransomware attack) by requiring consensus from a multi-party authorization (MPA) consensus regime before carrying out requested operations over the snapshot. The MPA consensus regime operates by determining that the operation is subject to a role-based access control (RBAC) as well as a multi-party authorization (MPA) consensus protocol, and then allowing or denying execution of the requested operations based on achieving consensus from among candidate approvers.

Abstract: A method may include, based on a recovery policy associated with the primary database, creating a first snapshot of the primary database at a primary computing system, replicating the first snapshot of the primary database to a secondary computing system, wherein a backup database of the primary database is hosted on the secondary cluster, in response to the primary database being unavailable, applying the first snapshot of the primary database to the backup database, creating, according to the recovery policy associated with the primary database, a snapshot of the backup database, in response to the primary database having restored availability, creating, according to the recovery policy associated with the primary database, a second snapshot of the primary database.

Abstract: Various embodiments set forth one or more non-transitory computer-readable media storing program instructions that, when executed by one or more processors, cause the one or more processors to perform steps of determining at least one physical resource of a node in a cluster of nodes is under contention by virtual computing instances or a virtual computing instance cannot be placed on the cluster of nodes, determining a placement for one or more virtual computing instances on the cluster of nodes, each virtual computing instance having a virtual resource associated with a profile that is compatible with a profile associated with a physical resource of a node on which the virtual computing instance is placed, and generating and executing a plan to achieve the placement, the plan including at least one of migrating at least one virtual computing instance or reconfiguring a profile associated with at least one physical resource.

Abstract: Methods, systems, and computer program products for moving a container-based application from a source HCI cluster to a target HCI cluster. An HCI storage cluster data replication mechanism operates to copy data and metadata from a plurality of storage devices that constitute a storage pool of the source HCI cluster. A container-based application replication mechanism operates to copy data and metadata from an executable container that is running on a node of the source HCI cluster. Periodically (1) the state of the container-based application is saved using the container-based application replication mechanism, and (2) the state of the storage cluster data of the HCI storage cluster is saved using the HCI storage cluster data replication mechanism. The saved state of the container-based application including its application data and metadata are combined with the saved state of the storage cluster data to bring-up the container-based application at the target HCI cluster.

Abstract: Systems and methods for scalable tracking of objects to be replicated are disclosed. A method may include in a first time period, updating, by one or more processors, a data structure with metadata of a received object to be replicated, wherein the data structure includes a plurality of classifications of objects to be replicated based on when the objects were received, in a second time period, after the first time period, updating, by the one or more processors, the data structure to modify a classification of the object based on the object being received in the first time period, and replicating, by the one or more processors, the object based on the modified classification of the object.

Abstract: A system may include a memory having computer-readable instructions stored thereon and a processor of a control plane that executes the computer-readable instructions to receive a request from a tenant to update a portion of a database, determine an individual tenant identifier of the tenant, determine whether the portion of the database is associated with the individual tenant identifier or a global tenant identifier, and allow the tenant to update the portion of the database in response to determining that the portion of the database is associated with the global tenant identifier or the individual tenant identifier or restrict the tenant from updating the portion of the database in response to determining that the portion of the database is associated with neither the global tenant identifier nor the individual tenant identifier.

Abstract: In one embodiment, a system for managing communication connections in a virtualization environment includes a plurality of host machines implementing a virtualization environment, wherein each of the host machines includes a hypervisor, at least one user virtual machine (user VM), and a distributed file server that includes file server virtual machines (FSVMs) and associated local storage devices. Each FSVM and associated local storage device are local to a corresponding one of the host machines, and the FSVMs conduct I/O transactions with their associated local storage devices based on I/O requests received from the user VMs. Each of the user VMs on each host machine sends each of its representative I/O requests to an FSVM that is selected by one or more of the FSVMs for each I/O request based on a lookup table that maps a storage item referenced by the I/O request to the selected one of the FSVMs.

Abstract: A database management system receives a user request for provisioning a database, autonomously selects a datacenter for provisioning the database based at least on a first pre-defined rule, autonomously selects at least one cluster in the datacenter based at least on a second pre-defined rule, determines a network location of each of the at least one cluster, and provisions the database on each of the at least one cluster using the network location of each of the at least one cluster.

Abstract: A system and method include creating, by an Availability Group (“AG”) controller in a virtual computing system, a first AG clone from a source database. The source database is stored on a primary replica node of an AG of the virtual computing system. The system and method also include creating, by the Controller, a second AG clone from the first AG clone and storing, by the Controller, the second AG clone on a secondary replica node of the AG. The second AG clone has a size of substantially zero.