Embodiments of a device and method are disclosed. In an embodiment, a method of network device configuration involves at a cloud server, generating a user interface to obtain user input information regarding service area configuration in a floor plan of a customer site, at the cloud server, receiving location information of a network device at the customer site, at the cloud server, automatically determining service area specific configuration of the network device based on the service area configuration in the floor plan of the customer site and the location information of the network device, and from the cloud server, transmitting the service area specific configuration to the network device.

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.

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.

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.

A memory record of a knowledge management tool stores data lineage criteria. A processor of the knowledge management tool receives a request to change one or more of a configuration of a server, a code of a hosted application, and a configuration of the hosted application. The processor determines whether a misalignment is detected associated with the requested change being outside at least one of the predefined ranges of values for server configuration data and application configuration data of the data lineage criteria. If the misalignment is not detected, the requested change is allowed to be implemented in one or both of the server and the hosted application. If the misalignment is detected, an alert is provided to an administrator device. If a response to the alert indicates to implement the requested change, implementation of the requested change is allowed. Otherwise, implementation of the requested change is prevented.

Automatically providing CLI commands for configuring devices is provided. A set of CLI commands for configuring a device on a network is retrieved from a database using an artificial intelligence component based on model and operating system version of the device. The set of CLI commands for configuring the device is displayed within a summary window of a cognitive CLI. The set of CLI commands entered by a user while configuring the device is verified in real time on a CLI of the cognitive CLI using the artificial intelligence component.

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.

A method for configuring, via a website, a device to provide printing services to a local network is described. The method includes creating, via a website, a service host object that comprises a network address of a device on a local network and a service host name. The method also includes configuring, via the website, one or more printing settings for one or more printing services. The method further includes sending an indication to the device on the local network to run a service manager. The method additionally includes sending an indication to the service manager to run the one or more printing services on the local network based on the one or more printing service settings.

A system and method for applying noise to data is described. The system accesses a metric value of a metric of each user from a group of users of an application. The metric indicates a measure of an operation of the application by a corresponding user. The system generates noise values and defines a distribution of the noise values to the group of users. The system modifies the metric value of the metric of each user with a corresponding noise value from the noise values based on the distribution.

Systems and methods for controlling operations of a Computer System (“CS”). The methods comprise: collecting information about events occurring in CS; performing automated ontogenesis operations using the collected information to determine a context of a given situation associated with CS using stored ontogenetic knowledge, define parameters for different sets of actions that could occur in the context of the given situation, simulate the sets of actions to generate a set of simulation results defining predicted consequences resulting from the performance of certain behaviors by nodes of CS, select a best simulation result from the set of simulation results, and determine whether a system action specified by the best simulation result might cause an undesirable unintended consequence; and using the parameters associated with the best simulation result to optimize control and performance of CS, when a determination is made that the system action will not cause the undesirable unintended consequence.