A network analytics controller is established in a network. The network includes a plurality of nodes. A plurality of network analytics agents is established; each agent at a node of the network. Network analytics configuration parameters, including a network analytics scope, are received at the networks analytics controller. A task is assigned to each agent at a node determined to be within the network analytics scope, the task comprising that portion of the network analytics specified in the network analytics configuration parameters relevant to the corresponding node. The assigned task is performed at each agent assigned a task. The networks analytics controller receives the results of each performed task, and aggregates the received results.

Network embedded framework for distributed network analytics

Systems for high-performance computing. A storage control architecture is implemented by a plurality of nodes, where a node comprises combinations of executable containers that execute in cooperation with virtual machines running above a hypervisor. The containers run in a virtual machine above a hypervisor, and/or can be integrated directly into the operating system of a host node. Sensitive information such as credit card information may be isolated from the containers in a separate virtual machine that is configured to be threat resistant, and which can be accessed through a threat resistant interface module. One of the virtual machines of the node may be a node-specific control virtual machine that is configured to operate as a dedicated storage controller for a node. One of the virtual machines of the node may be a node-specific container service machine that is configured to provide storage-related and other support to a hosted executable container.

Architecture for managing i/o and storage for a virtualization environment using executable containers and virtual machines

A method for writing data to a storage device including a processor, a volatile memory, and a non-volatile memory, the storage device being in communication with a host, the method includes receiving, by the processor, a command to write host data to the non-volatile memory, the host data being associated with a host identification, calculating, by the processor, a hash value associated with the host data, adding, by the processor, an object entry in an object map associated with the hash value, the object entry including the host identification and the hash value, and identifying, by the processor, whether there is a dedup entry in a deduplication map associated with the hash value, and writing, by the processor, stored data to the non-volatile memory based on the identification, the stored data being associated with and different from the host data.

Deduplication of objects by fundamental data identification

A digital network assistant which can detect network anomalies, identify actions likely to remediate them, and assist the user in carrying out those actions. In particular, a digital network assistant constantly monitors data streams associated with the network to determine key performance indicators for the network. When these key performance indicators indicate a network anomaly, the digital network assistant associates it with a digital string to one or more actions likely to remediate similar network issues. The digital network assistant can take these actions automatically or present them to a user to be taken. The system can also aid the user in taking the required actions via an augmented reality interface. In addition, the system can create narratives embedding findings from data analysis eliminating subjectivity. The system can also find optimal parameter sets by continuously analyzing anomaly-free parts of the network and their key performance indicators.

Integrated digital network management platform

A method for configuring an asynchronous Disaster Recovery (DR) process over a storage system comprising a plurality of storage sites, the method comprising: receiving data indicative of the storage sites; calculating information dispersal parameters that enable dispersing slices of DR enabling data based on original data written to a primary storage site out of the storage sites between at least two DR storage sites out of the storage sites, wherein at least one of the DR storage sites is a remote storage site, wherein each of the slices of DR enabling data is smaller than the original data and wherein the DR enabling data is larger than the original data; and configuring the asynchronous DR process in accordance with the calculated information dispersal parameters.

System and method for datacenters disaster recovery

A distributed storage system comprising: an infrastructure layer including interconnected computer nodes, wherein: each one of the interconnected computer nodes comprising processing resources configured to execute a Unified Distributed Storage Platform (UDSP) agent configured to: receive a task having assignments, calculating grades for assignments such that each grade is indicative of a suitability to execute assignments while meeting at least one Service Level Specification (SLS) requirement The grade is calculated based on storage related resources parameters data The task is routed to a more suitable computer node based on the calculated grades The updated infrastructure layer is created in response to adding interconnected computer nodes and executing assignments of following tasks or routing the following tasks to a more suitable computer node based on the calculated grades

Large scale storage system

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Large scale storage system

System and method for datacenters disaster recovery