Abstract: A database system associated with a plurality of source databases in a virtual computing system includes a dashboard having a main menu for providing a plurality of control functions and a body that dynamically changes based upon the plurality of control functions that are selected. The dashboard includes a homepage for displaying a plurality of cells in the body, including a first cell for displaying a list of the plurality of source databases. The main menu includes a first control function, the selection of which triggers a database provisioning service by presenting options to either create a new source database or register an existing database within the body and a second control function, the selection of which triggers a copy data management service by presenting an option to create a new cloned database.

Abstract: Examples of file analytics systems are described that may obtain metadata data and events data from a virtualized file server. The file analytics systems may detect one or more events from the events data matching a criteria indicating malicious activity. The file analytics systems may further identify one or more files of the virtualized file server affected by the detected malicious activity and recover a share of the distributed file server including the one or more affected files by replacing the one or more affected files with stored versions of the one or more affected files from a snapshot of the share taken prior to the detected malicious activity.

Abstract: A system and method for updating a component of a virtual computing system in a hyperconverged system includes installing, by a processor executing computer-readable instructions stored on a memory of a lifecycle manager of the virtual computing system, a software package on a node of the virtual computing system for updating the component of the virtual computing system, and booting, by the processor, the component into an update environment based on the software package. The software package decouples a dependency of the lifecycle manager on the update environment. The system and method also include updating, by the processor, the component in the update environment and booting, by the processor, the component out of the update environment into an operating environment upon completion of the update of the component.

Abstract: Disclosed is an improved approach for implementing and maintaining writable snapshots. An efficient approach is provided for implementing snapshots that can be used to immediately create snapshots without incurring any detectable delays in providing access to the new snapshots. Also described are improved metadata structures that can be used to implement and maintain the writable snapshots.

Abstract: An improved architecture is provided which enables significant convergence of the components of a system to implement virtualization. The infrastructure is VM-aware, and permits scaled out converged storage provisioning to allow storage on a per-VM basis, while identifying I/O coming from each VM. The current approach can scale out from a few nodes to a large number of nodes. In addition, the inventive approach has ground-up integration with all types of storage, including solid-state drives. The architecture of the invention provides high availability against any type of failure, including disk or node failures. In addition, the invention provides high performance by making I/O access local, leveraging solid-state drives and employing a series of patent-pending performance optimizations.

Abstract: A containerized clustered computing system may be used to provide a platform as a service (PaaS) environment. The clustered system may be configured by initiating a bootstrap node including a first cluster infrastructure orchestrator and first container orchestrator and migrating cluster metadata to a key value store of the first container orchestrator. A second node in the cluster may be initiated by configuring a second cluster infrastructure orchestrator of the second node with a dependency on the first container orchestrator of the bootstrap node.

Abstract: A system and method includes a plurality of nodes distributed between a first cluster and a second cluster, each of the plurality of nodes storing a copy of a source database and a processor executing computer-readable instructions stored on a memory to designate a first node of the plurality of nodes as a primary node, designate remaining ones of the plurality of nodes as secondary nodes to take over from the primary node upon failure of the primary node, designate a second node of the plurality of nodes as an initial active node, backup the source database from the initial active node, automatically designate, based on a switch over policy, a third node of the plurality of nodes as a next active node upon the initial active node becoming unavailable, and continue backups of the source database from the next active node upon the initial active node becoming unavailable.

Abstract: A method for providing external access into a secured networked virtualization environment, includes performing a leadership election amongst nodes of the secured networked virtualization environment to elect a leader node, assigning a cluster virtual IP address to the leader node and generating a reverse tunnel, using a processor, by the leader node to allow for an external entity to communicate with the secured networked virtualization environment.

Abstract: An object tiering system transfers or tiers data objects from a data store to a cloud store. The system includes a processor and a memory having stored instructions that, when executed by the processor, cause the processor to ingest a first plurality of data objects in the data store, map a second plurality of data objects having a common tiering date to a region, and upon reaching the common tiering date, transfer the region to the cloud store. In some embodiments, the mapping is done a priori when each data object is ingested or at a first time before the common tiering date. In some embodiments, the common tiering date is a second time for transferring the second plurality of data objects from the data store to the cloud store. In some embodiments, the first plurality of objects includes the second plurality of objects.

Abstract: Disclosed is an improved approach to implement I/O and storage device management in a virtualization environment. According to some approaches, a Service VM is employed to control and manage any type of storage device, including directly attached storage in addition to networked and cloud storage. The Service VM implements the Storage Controller logic in the user space, and can be migrated as needed from one node to another. IP-based requests are used to send I/O request to the Service VMs. The Service VM can directly implement storage and I/O optimizations within the direct data access path, without the need for add-on products.

Abstract: Examples of systems described herein include a virtualized file servers. Examples of virtualized file servers described herein may support disaster recovery of the virtualized file server. Accordingly, examples of virtualized file servers may support metadata fixing procedures to update metadata in a recovery setting. Examples of virtualized file servers may support hypervisor-agnostic disaster recovery.

Abstract: A system and method include classifying and assigning virtual disks accessed from compute only nodes. The method determines, by a management processor of a virtual computing system, characteristics for a plurality of virtual disks hosted on a plurality of hyper converged nodes in a cluster of nodes in the virtual computing system. The method further classifies, by the management processor, each of the plurality of virtual disks based on the determined characteristics and identifies, by the management processor, one of the plurality of virtual disks to host data for a virtual machine on a compute only node based on the classification to spread out input-output demand in the cluster, reducing probability of input-output bottlenecks and increasing cluster-wide storage throughput. The method also assigns, by the management processor, the identified virtual disk to host data for the virtual machine located on the compute only node.

Abstract: Methods, systems and computer program products for data protection across computing infrastructure comprising a plurality of geographically distant computing clusters. The geographically distant computing clusters form a distributed system comprising clusters that are assigned into availability zones. Disaster recovery policies are maintained in each of the availability zones. A first cluster detects a modification of a disaster recovery policy. The modification of the disaster recovery policy that occurred at the first cluster is to be communicated over a wide area network. Synchronization of the disaster recovery policy is accomplished by carrying out a peer-to-peer communication protocol over the wide area network.

Abstract: Various embodiments disclosed herein are related to a non-transitory computer readable storage medium. In some embodiments, the medium includes instructions stored thereon that, when executed by a processor, cause the processor to detect, on an edge network, a state change of a cluster including one or more edge processing units, identify a plurality of first configuration override rules from a first source and a plurality of second configuration rules from a second source, merge at least one first configuration override rule with at least one second configuration override rule to generate a plurality of third configuration override rules, update a configuration of the one or more edge processing units using the plurality of third configuration override rules, and collect data from the one or more edge processing units in accordance with the configuration update.

Abstract: Examples described herein include virtualized file servers which may include cloned instances of the virtualized file server. Cloning a virtualized file server may allow for testing of new and/or revised features, disaster recovery plans, or other configurations while maintaining availability of the parent (e.g., source) virtualized file server.

Abstract: Various embodiments disclosed herein are related to a non-transitory computer readable storage medium. In some embodiments, the medium includes instructions stored thereon that, when executed by a processor, cause the processor to receive a stored configuration state of a cluster, receive a snapshot of the configuration state of the cluster, determine that an entity of the cluster is different between the stored configuration state and the snapshot, determine that a first timestamp of the stored configuration state is less than a second timestamp of the snapshot, and send an indication that the entity is changed.

Abstract: An illustrative embodiment disclosed herein is an apparatus including a processor and a memory. In some embodiments, the memory includes programmed instructions that, when executed by the processor, cause the apparatus to store a first object and a second object in a first region based on the first object and the second object having a first policy. In some embodiments, the memory includes programmed instructions that, when executed by the processor, cause the apparatus to store a third object in a second region based on the third object having a second policy. In some embodiments, a virtual disk includes the first region and the second region.

Abstract: Examples described herein include virtualized environments including a virtualized file server. Examples of file server virtual machine managers are described which may setup and/or configure file server virtual machines in accordance with a target number of connections and/or a target throughput for the virtualized file server. The virtualized file server may be scaled up, scaled down, scaled in, and/or scaled out.

Abstract: Systems and methods described herein generally relate to compute node resource scheduling. AI inference services described herein may receive a request to execute a machine learning model in a clustered edge system. To determine which hardware resource comprising computing nodes of the clustered edge system on which to execute the machine learning model, AI inference services may compare the computational workload of the machine learning model, with the computational abilities and functions of the hardware resources. In examples, the comparison is based on a scheduling algorithm, including an identification stage to identify candidate hardware resources capable of executing the machine learning model, and a scoring stage to select the best candidate hardware resource for executing the machine learning model. A scheduler may assign the machine learning model to the selected hardware resource for execution by the AI inference services.