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 computer readable network analysis program of performing local modeling analysis of determining an estimated value of a current network quality corresponding to explanatory variable vector in current aggregated data based on a local model including local training data; determining an abnormality in the network based on whether or not a measured value of the current network quality is lower than a threshold; determining whether or not a distribution of the connections having the measured value of the network quality exceeding the threshold is present in a large size; extracting an individual-analysis-target connection group including more than predetermined proportions of connections in the distribution of the connections having the large size; and performing the local modeling analysis to the individual-analysis-target connection group and the remaining connection groups to determine the abnormality in the network.

In various embodiments, the techniques and supporting systems implement a recursive routing mechanism in hierarchical topological addressed environments to analyze and determine the presence of packet-forwarding errors within an IP network comprising a plurality of network-connected devices. This includes receiving, at a software defined network device, an indication of a potential packet-forwarding error between a first and second device of the plurality of network-connected devices and injecting, by the software defined network device, a test packet at an ingress to the first device. The test packet includes an initial ingress interface location identifying the first device, an alternate ingress interface location identifying the software defined network device and an egress interface location identifying the second device. A determination may then be made as to whether the test packet is received at the second device, thus indicating the existence or lack of routing errors.

Presented herein are embodiments for quickly identifying and recommending key performance indicators (KPIs) for network devices based on the type of network device and/or role of the device. The type or configuration of the network device may be obtained and compared to the capabilities of the network device. Operational or performance information of the network device, represented by strings, may be obtained based on the configuration information. Operational information that is not relevant to the configuration of the network device may be filtered out. The remaining operational information may be ranked as KPIs based on a relevance of the operational information with respect to the configuration information.

Presented herein are embodiments for quickly identifying and recommending key performance indicators (KPIs) for network devices based on the type of network device and/or role of the device. The type or configuration of the network device may be obtained and compared to the capabilities of the network device. Operational or performance information of the network device, represented by strings, may be obtained based on the configuration information. Operational information that is not relevant to the configuration of the network device may be filtered out. The remaining operational information may be ranked as KPIs based on a relevance of the operational information with respect to the configuration information.

Methods and systems for heuristic and automated policy recommendations in a virtual environment are described herein. A computing device may obtain, from a plurality of user devices, usage information associated with a virtual service. The computing device may obtain, from the plurality of user devices, currently applied user experience policies for the virtual service. The computing device may further obtain, from the plurality of user devices, system settings for the virtual service. Based on the usage information, the currently applied user experience policies, and the system settings, the computing device may cluster users associated with the plurality of user devices into user groups; and determine a set of new policies for each user group. The computing device may further recommend the set of the new policies.

A network management apparatus according to an embodiment includes a storage device configured to store information indicating connection relationships between a plurality of communication devices and communication paths in a network configuration and rank information indicating ranks of the plurality of communication devices in the network configuration and a determination unit configured to, when a fault has occurred in a communication device, determine that a communication device influenced by the fault is within a fault influence range based on the information stored in the storage device.

A network management apparatus according to an embodiment includes a storage device configured to store information indicating connection relationships between a plurality of communication devices and communication paths in a network configuration and rank information indicating ranks of the plurality of communication devices in the network configuration and a determination unit configured to, when a fault has occurred in a communication device, determine that a communication device influenced by the fault is within a fault influence range based on the information stored in the storage device.

In one embodiment, a device obtains behavioral metrics for application traffic in a network for a plurality of applications. The device identifies a first application and a second application from among the plurality of applications as fate sharing applications, based on a correlation between the behavioral metrics for their application traffic. The device generates a configuration change for the network that would prevent the first application and the second application from being fate sharing applications, when application traffic for the first application negatively affects the behavioral metrics for the application traffic of the second application. The device causes the configuration change to be implemented in the network.