The present disclosure relates to method and a system for monitoring application services in network. The system comprises ASM client and ASM server. The ASM client is configured in UE to monitor parameters related to applications in UE. The ASM server monitors VAL server based on parameters associated with VAL server. The ASM server obtain status information of VAL server by performing either pull procedure, push procedure, and subscribe-notify procedure. Further, the ASM server provides the status information to one or more entities for performing one or more actions. Thus, the present disclosure facilitates the system to monitor the application services and indicate one or more entities to perform corrective actions to provide seamless and uninterrupted services to users.

A method is performed at one or more entities configured to configure and provide assurance for a service enabled on a network. The service is configured as a collection of subservices on network devices of the network. A definition of the service is decomposed into a subservice dependency graph that indicates the subservices and dependencies between the subservices that collectively implement the service. Based on the subservice dependency graph, the subservices are configured to record and report subservice metrics indicative of subservice health states of the subservices. The subservice metrics are obtained from the subservices, and the subservice health states of the subservices are determined based on the subservice metrics. A health state of the service is determined based on the subservice health states. One or more of the subservices are reconfigured based on the health state of the service.

A method of assessing a risk level of an enterprise using cloud-based services from one or more cloud service providers includes assessing provider risk scores associated with the one or more cloud service providers; assessing cloud service usage behavior and pattern of the enterprise; and generating a risk score for the enterprise based on the provider risk scores and on the cloud service usage behavior and pattern of the enterprise. The risk score is indicative of the risk of the enterprise relating to the use of the cloud-based services from the one or more cloud service providers.

A digital service evaluation system evaluates services and user sessions provided by a service, to provide an overall score of the service. The digital service evaluation system detects client sessions associated with one or more devices. The digital service evaluation system obtains a first plurality of scores associated with performance metrics of the client session, and calculates an overall score for the client session. The digital service evaluation system obtains a second plurality of scores and calculates a second overall score. The digital service evaluation system determines a weight for each performance metric based on the first and second plurality of scores and the overall scores. The digital service evaluation system uses the weights to determine which performance metric caused a change in the overall scores. The digital service evaluation system takes an action based on the determination that a performance metric caused a change in the overall scores.

Described are examples for providing service level monitoring for a network hosting applications as a cloud service. A service level monitoring device may receive end-to-end measurements of service usage collected at user devices for a plurality of applications hosted as a cloud services. The service level monitoring device may determine degraded applications of the plurality of applications based on anomalies in the measurements. The service level monitoring device may determine a service level metric based on an aggregation of the degraded applications. In some examples, the service level monitoring device may detect a network outage affecting the service.

A method may comprise collecting data from a core network, an operator network and a customer premise network. KPI values corresponding to one or more KPIs may be determined, based on the collected data. KQI values corresponding to one or more KQIs may be determined, based on the one or more of the determined KPI values. The determined KQI values may be output to an operator. In an embodiment, data collected from the core network may include data collected from one or more analyzer devices and head end probes. Data collected from a customer premise network may include data collected from last mile equipment or customer premise probes.

A method of managing communication services provided by a service provider, comprising obtaining a prediction of a portion of the quantity of the served devices that received substandard communication services from the service provider during a period of time, obtaining an acceptable deviation from the prediction of the portion of served devices, making a determination that a quantity of the served devices that received substandard communication services from the service provider during the period of time is outside of a range, and performing an action set to initiate remediation of the service provider. Specifically, the determination is based on the prediction of the portion of the quantity of served devices, and the acceptable deviation.

In a report information sending method, a first session management network element receives first report information, which includes first indication information and an identifier of a first alternative QoS profile, from a user plane network element. The first indication information indicates that a QoS requirement of a first QoS flow cannot be guaranteed. The first session management network element sends second report information, which includes second indication information and an identifier of a first alternative service requirement, to an application function network element. The identifier of the first alternative service requirement corresponds to the identifier of the first alternative QoS profile. The second indication information indicates that a QoS requirement of a first service data flow cannot be guaranteed. The first QoS flow is configured to transmit the first service data flow, which is a service data flow of an application corresponding to the application function network element.

Aspects of the subject disclosure may include, for example, a method in which a processing system receives data at an edge node of a network that also includes regional nodes and central nodes. The processing system also determines a latency criterion associated with an application for processing the data; the application corresponds to an application programming interface. The method also includes processing the data in accordance with the application, monitoring a latency associated with the processing, and determining whether the latency meets the latency criterion. The processing system dynamically assigns data processing resources so that the latency meets the latency criterion; the resources include computation, network and storage resources of the edge node, a central node, and a regional node in communication with the edge node and the central node. Other embodiments are disclosed.

A computer-implemented method upgrades an edge network based on analysis by a learning model. The method includes identifying, in a network, a plurality of devices, where each device in the network is configured to provide data on at least one other device in the network. The method also includes determining capabilities of each device of the plurality of devices. The method further includes monitoring, for each device, capacity information and tasks performed during operation of the network. The method includes analyzing, based on the monitoring, each use of each device. The method also includes recommending, in response to the analyzing and by a learning model, a first upgrade to the network. The method further includes implementing the first upgrade.