Some embodiments provide a method for associating data message flows from applications executing on a host computer with network interfaces of the computer. The method of some embodiments identifies a set of applications operating on a machine executing on the host computer, identifies candidate teaming policies for associating each identified application with a subset of one or more interfaces, and generates a report to display the identified candidate teaming policies per application to a user. In response to user input selecting a first teaming policy for a first application, the method generates a rule, and distributes the rule, to the host computer to associate the first application with a first subset of the network interfaces specified by the first teaming policy. Similarly, in response to user input selecting a second teaming policy for a second application executing on the machine, the method generates a second rule, and distributes the second rule, to the host computer to associate the second application with a second subset of the network interfaces specified by the second teaming policy.

Some embodiments provide a method for associating data message flows from applications executing on a host computer with network interfaces of the computer. The method of some embodiments identifies a set of applications operating on a machine executing on the host computer, identifies candidate teaming policies for associating each identified application with a subset of one or more interfaces, and generates a report to display the identified candidate teaming policies per application to a user. In response to user input selecting a first teaming policy for a first application, the method generates a rule, and distributes the rule, to the host computer to associate the first application with a first subset of the network interfaces specified by the first teaming policy. Similarly, in response to user input selecting a second teaming policy for a second application executing on the machine, the method generates a second rule, and distributes the second rule, to the host computer to associate the second application with a second subset of the network interfaces specified by the second teaming policy.

Some embodiments provide a method for associating data message flows from applications executing on a host computer with network interfaces of the computer. The method of some embodiments identifies a set of applications operating on a machine executing on the host computer, identifies candidate teaming policies for associating each identified application with a subset of one or more interfaces, and generates a report to display the identified candidate teaming policies per application to a user. In response to user input selecting a first teaming policy for a first application, the method generates a rule, and distributes the rule, to the host computer to associate the first application with a first subset of the network interfaces specified by the first teaming policy. Similarly, in response to user input selecting a second teaming policy for a second application executing on the machine, the method generates a second rule, and distributes the second rule, to the host computer to associate the second application with a second subset of the network interfaces specified by the second teaming policy.

Some embodiments provide a method for associating data message flows from applications executing on a host computer with network interfaces of the computer. The method of some embodiments identifies a set of applications operating on a machine executing on the host computer, identifies candidate teaming policies for associating each identified application with a subset of one or more interfaces, and generates a report to display the identified candidate teaming policies per application to a user. In response to user input selecting a first teaming policy for a first application, the method generates a rule, and distributes the rule, to the host computer to associate the first application with a first subset of the network interfaces specified by the first teaming policy. Similarly, in response to user input selecting a second teaming policy for a second application executing on the machine, the method generates a second rule, and distributes the second rule, to the host computer to associate the second application with a second subset of the network interfaces specified by the second teaming policy.

Systems and methods include obtaining a network state of a network having a plurality of nodes interconnected by a plurality of links and with services configured between the plurality of nodes on the plurality of links; utilizing a reinforcement learning engine to analyze the services and the network state to determine modifications to one or more candidate services of the services to increase a value of the network state; and, responsive to implementation of the modification to the one or more candidate services, updating the network state based thereon. The modifications can include changes to any of routing, modulation, and spectral assignment to the one or more candidate services.

Aspects of the subject disclosure may include, for example, determining, an application requirement for a server of a data center geographically separated from a central location. A configuration file adapted for the server according to the application requirement is obtained at the central location and a host processor located at the data center is selected according to the application requirement. A static IP address preassigned to an administrative portion of the selected host processor is identified. The selected host processor is initialized remotely over a wide area network via the administrative port without utilizing any software resources pre-existing at the data center. The initializing configures the selected host processor according to the configuration file to service the application requirement. Other embodiments are disclosed.

The disclosure provides an approach for service deployment. Embodiments include receiving an indication of user intent for deployment of one or more services in a network from a user that is not an administrator of the network, wherein the indication of the user intent comprises a domain specific language (DSL). Embodiments include parsing the indication of the user intent to determine one or more constraints for deploying the one or more services. Embodiments include receiving topology information for the network, wherein the topology information comprises associations between racks and machines in the network. Embodiments include receiving network performance information for the network. Embodiments include determining one or more deployment rules for the one or more services based on the one or more constraints, the topology information, and the network performance information. Embodiments include deploying the one or more services in the network based on the one or more deployment rules.

The invention relates to a method for configuring a user equipment, comprising the steps of a) accessing user related information, preferably account information, on the user equipment, b) transmitting the user related information to a dedicated configuration server, c) matching the user related information to a specific configuration information, d) upon matching, transmitting the configuration information to the user equipment, e) configuring the user equipment with the configuration information, and wherein initiation of the steps a)-e) is performed by a one-touch-client and wherein the configuration server is provided as a one-touch-server. The invention also relates to a system for configuring a user equipment.

Systems, devices, media, and methods are presented for splitting decision trees between server and client. The client of the systems and methods sends a configuration query. The server of the system and method receives the configuration query. The server retrieves Config rule(s) according to the configuration query. Each of the Config rule(s) can be represented by decision tree(s). The server evaluates the decision tree(s). If a definitive True or False cannot be derived from the evaluation using server knowledge, the server prunes the decision tree(s) and returns them to client side for further evaluation.

Systems, methods, and other embodiments associated with autonomous cloud-node scoping for big-data machine learning use cases are described. In some example embodiments, an automated scoping tool, method, and system are presented that, for each of multiple combinations of parameter values, (i) set a combination of parameter values describing a usage scenario, (ii) execute a machine learning application according to the combination of parameter values on a target cloud environment, and (iii) measure the computational cost for the execution of the machine learning application. A recommendation regarding configuration of central processing unit(s), graphics processing unit(s), and memory for the target cloud environment to execute the machine learning application is generated based on the measured computational costs.