Abstract: Methods and apparatus to deploy workload domains in virtual server racks are disclosed. An example apparatus includes a policy manager to determine an availability option and a performance option of the workload domain based on a domain type and determine capacity options based on a user selection of the availability option and a user selection of the performance option by a first user, a deployment manager to identify first ones of a plurality of computing resources to form a placement solution for the workload domain based on the user selection of the availability and performance options, and based on a user selection of one of the determined capacity options by the first user, the plurality of computing resources stored in a resource database accessible by the first user and a second user, and a resource manager to reserve the first ones of the plurality of computing resources to deploy the workload domain for the first user.

Abstract: The present invention discloses a method for implementation of a software application implemented by a processor of a computer system, wherein said software application enables mapping of one or more diagramming elements to one or more cloud computing server, wherein said method comprising: Configuring, by an application interface, at least a 2D or 3D network architecture model on a first cloud computing platform, using one or more cloud components directly from a graphical drawing tool; deploying, by said application interface, said network architecture model on said first cloud computing platform to create a cloud application network; requesting, by said application interface, a copy of said cloud application network from said first cloud computing platform; shifting, by said application interface, said cloud application network from said first cloud computing platform to said second cloud computing platform for deploying said cloud components in a second cloud computing platform.

Abstract: The smart network topology systems and methods of the present disclosure are aimed at easing network administrator efforts in configuring network configurations to suit their network environment. For instance, the smart network topology system may provide predefined network topology types that an administrator can use when setting up network connectivity between client devices and other network devices such as media agents, storage servers, and the like. Further, the smart network topology system provides the user with a way to customize the routes created between the client computing devices and storage computing devices such that each client computing device is configured to communicate with only those storage computing devices that the client computing device needs to communicate with to perform one or more data protection operations.

Abstract: Methods and system for supporting traffic steering through a service function chain, the service function chain comprising at least one data processing function. An aspect of the disclosure provides for a method for steering traffic of a packet data unit (PDU) performed by a session management function. The method includes receiving PCC rules from a policy control function, the PCC rules including information comprising at least one of service function chain information; final delivery indication; and selective traffic steering information and associated parameters. The method further includes configuring at least one user plane function (UPF) according to the information. In some embodiments the configuring the at least one UPF includes instructing a first UPF to detect traffic according to the packet detection rules and route the received packet according to the forwarding action rules.

Abstract: A processing system may generate segments of network infrastructure items deployed in a communication network, each segment comprising network infrastructure items grouped in accordance with segment filters and a segment size sparsity threshold, and identify anomalous segments comprising at least a subset of the segments having anomalies of an anomaly type regarding a performance indicator. The processing system may next determine segments from the subset that are defined by sets of segment filter values that are different for less than a threshold number of segment filters, merge the segments from the subset that are different for less than the threshold number to create at least one aggregate segment, and generate a ranking of the subset having the anomalies of the anomaly type, wherein the ranking includes the at least one aggregate segment. The processing system may then perform at least one action in the communication network responsive to the ranking.

Abstract: A device is configured to obtain network traffic information that is associated with a first network device and to identify a second network device that communicates data with the first network device. The device is further configured to identify device settings for sending data traffic to the second network device and to identify error correction instructions for rerouting data traffic to another network device. The device is further configured to generate node properties for the first network device that include a first network device identifier, a second network device identifier, the device settings for the second network device, and the error correction instructions. The device is further configured to add a first node to a computer network map for the first network device and to associate the node properties with the first node and output the computer network map.

Abstract: The present disclosure is directed to systems and techniques for providing zero-touch deployment (ZTD) and/or adaptive network traffic control policy management for deployed Internet-of-Things (IoT) devices. In one example, the systems and techniques can include obtaining a network traffic policy from a network traffic control service and obtaining one or more data usage policies from an IoT hub. Data usage measurements can be obtained for a plurality of IoT devices. One or more IoT device traffic policies can be automatically generated based at least in part on the network traffic policy, the one or more data usage policies, and the data usage measurements. The IoT device traffic policies can be used to provision or configure at least a portion of the plurality of IoT devices.

Abstract: A distributed cloud computing system is disclosed that includes a controller configured to deploy a first gateway in a first cloud computing network and a second gateway in a second cloud computing network, and logic. The logic, upon execution by one or more processors, causes performance of operations including receiving, from the controller, metadata pertaining to a plurality of constructs corresponding to a plurality of time instances, receiving, from each of the first and second gateways, network data corresponding to the plurality of time instances, wherein the metadata and the network data identify each of the plurality of constructs, communication paths between each construct, and in which cloud computing network each construct is deployed, generating a visualization illustrating differences between the plurality of constructs and communication paths at the first time instance and at the second time instance, and causing rendering of the visualization on a display screen.

Abstract: An electronic device (such as a controller) is described. During operation, the electronic device receives, from a second electronic devices, information that specifies occurrences of different types of events in a network (which includes the second electronic devices). For example, the information may include counts of the occurrences of the different types of events in the network, which may be collected by the second electronic devices. Then, the electronic device aggregates the information about the different types of events in the network, and stores the aggregated information in memory. Moreover, the electronic device predicts an occurrence of an anomaly or an error in the network based at least in part on the aggregated information and a pretrained machine-learning model (such as a neural network). Next, the electronic device selectively performs a remedial action based at least in part on the prediction.

Abstract: Methods, systems, and apparatuses may determine a connection topology for a service and send an alert in which the alert includes a service connection topology that includes a plurality of port assignments for each equipment of the connection topology.

Abstract: One example method includes various processes performed by a vendor system including discovering infrastructure assets of a subscriber system, determining that the vendor system is permitted by the subscriber system to access information about the infrastructure assets of the subscriber system, accessing the information about the infrastructure assets of the subscriber system, assessing an ability of the infrastructure assets of the subscriber system to implement a service offering of the vendor system, and the assessing is based on the information about the infrastructure assets, and implementing the service offering in the infrastructure assets of the subscriber system when (i) given permission to do so by the subscriber system and (ii) the infrastructure assets have been determined to be able to implement the service offering.

Abstract: Systems and techniques for dynamic runtime application integration are generally described. A set of source nodes may be determined for a first compute service. A source node priority score may be determined for each source node. A first destination node priority score may be determined for a first destination node for the first compute service. The source node priority score for a first source node and the first destination node priority score may be combined to determine a first priority score. The source node priority score for a second source node and the first destination node priority score may be combined to determine a second priority score. A first data pathway from the first source node to the first destination node may be prioritized based at least in part on a comparison of the first priority score and the second priority score.

Abstract: An example method includes receiving, by an SD-WAN system, WAN link characterization data for a plurality of WAN links of the SD-WAN system over a time period; and for each site of a plurality of sites of the SD-WAN system, generating, by the SD-WAN system, a local policy for the site, wherein generating the local policy is based on a machine learning model trained with the WAN link characterization data for the plurality of WAN links, and providing the local policy to an SD-WAN edge device of the site.

Abstract: Systems, devices, methods, media, and instructions for automated image processing and content curation are described. In one embodiment a server computer system receives a content message from a first content source, and analyzes the content message to determine one or more quality scores and one or more content values associated with the content message. The server computer system analyzes the content message with a plurality of content collections of the database to identify a match between at least one of the one or more content values and a topic associated with at least a first content collection of the one or more content collections and automatically adds the content message to the first content collection based at least in part on the match. In various embodiments, different content values, image processing operations, and content selection operations are used to curate content collections.

Abstract: A device receives, from a first compute instance, a Remote Latency Call, that includes a target latency measure, a function, and one or more arguments for the function. The device clusters a plurality of compute instances into multiple clusters of compute instances based on a respective latency measure associated with each compute instance of the plurality of compute instances, and determines a first cluster of compute instances from the multiple clusters of compute instances that satisfies the target latency measure. The device causes a second compute instance within the first cluster of compute instances to execute the function, using the one or more arguments, and return one or more results.

Abstract: A communication pathway between a plurality of network nodes within a network is established. A DIS election operation is executed to determine a first network node among the plurality of network nodes as the DIS for the network and creating a first pseudo node for the first network node, and with each network node of the plurality of network nodes, determining whether the connectivity between the first network node and the other network nodes of the plurality of network nodes within the network is in a synchronous state with the adjacencies with the other network nodes of the plurality of network nodes within the network.

Abstract: Method of dynamically assigning storage locations starts with the processor updating first user's home location data. Processor selects communication session between first user and second user and determines second user's home location data. Processor determines a session location data that indicates current storage location that stores data of communication session received from first and second client devices. Processor identifies available data storage locations based on first user and second user's home location data and determines whether to update the session location data based on an average of a distance over network fiber using the first user and second user's home locations, current storage location, and available storage locations. In response to determining to update the session location data, processor updates session location data to indicate one of the available storage locations, and causes transfer of data of communication session to one of the available storage locations.

Abstract: Systems and methods are disclosed for a consensus-based node retirement in a mesh network. An example system includes: a mesh network comprising a plurality of nodes, including a first node, a second node, and a mesh controller; a processor; and memory. The memory may store instructions that, when executed by the one or more processors, may cause the first node to: send, to the second node, a request for a performance status; and receive a response to the request; and identify a deficiency in a performance metric of the second node. The deficiency may be based on a failure of the performance metric of the second node to satisfy a first membership rule of a mesh membership contract. After a consensus by the mesh network for the identified deficiency, the first node may cause a removal of one or more capabilities of the second node from the mesh network.

Abstract: Systems and methods of a smart and efficient agent integrated with an agile software architecture to collect and present telemetry data from a field deployed device. The collected telemetry data from the field deployed device is streamed to the service provider's streaming and analytics platform, where it is analyzed and presented to a hierarchical color-coded dashboard that is available to both the customer associated with the field deployed device, and the service provider's care agent associated with the field deployed device.

Abstract: Network device identification. A method includes extracting, from network traffic data of a plurality of user devices in a computer network, one or more data fragments relating to a device model of each user device, associating the one or more data fragments with device identification data assigned to each user device, determining a device model for a specific data fragment based on analyzing one or more data fields associated with the specific data fragment, and generating one or more device model identification rules based on the specific data fragment.