A method and system corrects a content delivery infrastructure. The method of the system includes receiving a request to resolve reported issues for the content delivery infrastructure, collecting content delivery metrics for the content delivery infrastructure, executes a language transformer model on the request and the content delivery metrics to generate a set of possible resolutions with confidence ratings, and implementing an automated solution based on a resolution from the set of possible resolutions, in response to the resolution having a confidence rating above a threshold.

Systems, methods, and non-transitory computer-readable storage media are provided for predicting the likelihood or probability of a subscriber of a service to cancel or not renew a subscription. A method, according to one implementation, includes a step of receiving data pertaining to aspects of a service that is provided by a service provider to a subscriber in accordance with a subscription. The data may include one or more impact factors each having a positive, neutral, or negative influence on the likelihood of subscriber churn. The method also includes a step of using the one or more impact factors to predict the likelihood that the subscriber will cancel the subscription.

Techniques for managing energy use of a computing deployment are provided. In one embodiment, a computer system can establish a performance model for one or more components of the computing deployment, where the performance model models a relationship between one or more tunable parameters of the one or more components and an end-to-end performance metric, and where the end-to-end performance metric reflects user-observable performance of a service provided by the computing deployment. The computer system can further execute an algorithm to determine values for the one or more tunable parameters that minimize power consumption of the one or more components, where the algorithm guarantees that the determined values will not cause the end-to-end performance metric, as calculated by the performance model, to cross a predefined threshold. The computer system can then enforce the determined values by applying changes to the one or more components.

Techniques for managing energy use of a computing deployment are provided. In one embodiment, a computer system can establish a performance model for one or more components of the computing deployment, where the performance model models a relationship between one or more tunable parameters of the one or more components and an end-to-end performance metric, and where the end-to-end performance metric reflects user-observable performance of a service provided by the computing deployment. The computer system can further execute an algorithm to determine values for the one or more tunable parameters that minimize power consumption of the one or more components, where the algorithm guarantees that the determined values will not cause the end-to-end performance metric, as calculated by the performance model, to cross a predefined threshold. The computer system can then enforce the determined values by applying changes to the one or more components.

A method of determining an end-to-end, E2E, service level for a communications network (100) by a network management entity (101). The communications network (100) comprises one or more network domain. The method comprises obtaining (201) a first set of service level data for the one or more network domain. The first set of service level data for said one or more network domain comprises a summarized set of data derived from service level data monitored by said one or more network domain. The method further comprises determining (202) the end-to-end service level based on the obtained first set of service level data from the one or more network domain.

A method of determining an end-to-end, E2E, service level for a communications network (100) by a network management entity (101). The communications network (100) comprises one or more network domain. The method comprises obtaining (201) a first set of service level data for the one or more network domain. The first set of service level data for said one or more network domain comprises a summarized set of data derived from service level data monitored by said one or more network domain. The method further comprises determining (202) the end-to-end service level based on the obtained first set of service level data from the one or more network domain.

A traffic analysis apparatus includes: a first means that estimates a state sequence from time-series data of communication traffic based on a hidden Markov model, and groups, into one group, a plurality of patterns with resembling state transitions in the state sequence to perform extraction of a state sequence, with taking the plurality of patterns grouped into one group as one state; and a second means that determines an application state corresponding to the time-series data based on the state sequence extracted by the first means and predetermined application characteristics.

Example implementation relates to a method for establishing a dynamic VPN tunnel between branch gateway devices based on metric data. A branch orchestrator receives metric data from VPNC device. The metric data includes data center bandwidth and processor utilization of the VPNC device. The metric data is derived from the traffic being routed via the VPNC device. When the metric data associated with traffic between a first branch gateway device and a second branch gateway device is above a Service Level Agreement (SLA), a dynamic branch to branch VPN tunnel is established to route the traffic between the first branch gateway device and the second branch gateway device. The VPN tunnel between the branch gateways can be teared when the load at the VPNC device reduces.

An information handling system includes a plurality of network nodes and a processor. Each network node includes an optical link and a reflectometry analyzer. The reflection analyzers provide a plurality of reflectometry results that each provide a characterization of physical properties of the optical link. The processor receives the reflectometry results, analyzes the reflectometry results to define a fingerprint of the physical properties of the optical link, and determines a status for each of the optical links based upon the associated fingerprints. The status for each of the optical links includes one of a plurality of graded statuses. Each graded status represents a qualitative measure of the physical properties of the associated optical link. A first graded status represents a better qualitative measure than a second graded status. The processor further receives a request to route a data flow from a first one of the network nodes to a second one of the network nodes. The data flow is associated with a service level agreement that defines that the data flow is to be routed on optical links that have the first graded status. The processor further determines a path between the first network node and the second network node where each of optical links in the path have the first graded status.

Apparatuses, systems, and methods for performing network slice quota management. A network slice quota management function may store capacity information for one or more network slices. The network slice quota management function may receive a request for an indication of whether a network slice has additional capacity. The network slice quota management function may provide an indication of whether the network slice has additional capacity in response to the request. The capacity information may relate to the capacity of the network slice with respect to the number of wireless devices registered for the network slice, or to the capacity of the network slice with respect to the number of packet sessions established with the network slice, or both, among various possibilities.