A computing system implementing an application service can receive network data from computing devices of clients of the application service. The system can determine, from the network data, that a network latency for a subset of the computing devices crosses above a latency threshold. Based on determining that the subset of computing devices utilize a common network service provider, the system can transmit a set of configuration signals to the subset of computing devices, which modify a set of default application configurations of the designated application to compensate for the network latency.

A computing system implementing an application service can receive network data from computing devices of clients of the application service. The system can determine, from the network data, that a network latency for a subset of the computing devices crosses above a latency threshold. Based on determining that the subset of computing devices utilize a common network service provider, the system can transmit a set of configuration signals to the subset of computing devices, which modify a set of default application configurations of the designated application to compensate for the network latency.

Techniques described herein relate to a method for managing performances of data protection services. The method may include obtaining subsystem statistics from subsystems; in response to obtaining the subsystem statistics, making a determination that the subsystem statistics indicate a concurrency adjustment; and in response to the determination, assigning an adjusted concurrency to the subsystems based on the subsystem statistics and priorities; and initiating performance of data protection services using the adjusted concurrency.

Method and system for performance assurance in a network slice subset instance (NSSI) or a network slice instance (NSI) of a network. The method comprises receiving, at a network management function (OAM) of the network, a trigger indicating a network performance deficiency; based on the trigger, determining, by a data analytics (DAM) function of the OAM (OAM DAM) in coordination with a network analytics function of one of the core network and a radio access network (RAN), an NSI/NSSI modification; and implementing, by the OAM, a change in at least one of: NSI/NSSI policies, configurations in at least one of core network functions, the RAN and network resources, in accordance with the NSF NSSI modification.

Method and system for performance assurance in a network slice subset instance (NSSI) or a network slice instance (NSI) of a network. The method comprises receiving, at a network management function (OAM) of the network, a trigger indicating a network performance deficiency; based on the trigger, determining, by a data analytics (DAM) function of the OAM (OAM DAM) in coordination with a network analytics function of one of the core network and a radio access network (RAN), an NSI/NSSI modification; and implementing, by the OAM, a change in at least one of: NSI/NSSI policies, configurations in at least one of core network functions, the RAN and network resources, in accordance with the NSF NSSI modification.

A system which facilitates efficient operation of plural agents, the system comprising a device which services the plural agents; and functionality which resides on the device and which provides a given quality of service, defined in terms of at least one resource, to at least one subset of agents from among the plural agents.

A method for anomaly detection and troubleshooting in a network includes parsing a network service descriptor (NSD) describing a network service (NS) to be deployed in the network. Monitoring data including time series of service-level metrics and resource-level metrics of network functions (NFs) of the NS are received from different domains of the network. Representations of the time series from the different domains are learned with a common dimensionality. An NS signature of the NS is computed as a cross-correlation matrix comprising cross-correlations between the service-level metrics and the resource-level metrics of the NFs. Embeddings of the NS signature are learned using a model and determining a reconstruction error of the model. It is determined whether the NS is anomalous based on the reconstruction error of the model. The NS is identified as a target for the troubleshooting in a case that the NS was determined to be anomalous.

Dynamic management of data traffic workflows is performed. An event to perform a data traffic workflow at a remote performance location may be received. Computing resources to perform the data traffic workflow may be identified. Operations to perform the data traffic workflow may be dynamically directed by the identified computing resources to adaptively balance performance of the operations with operations for other data traffic workflows in order to meet respective performance requirements of the data traffic workflows.

A computer manages reconfigurations of a Byzantine fault-tolerant, distributed computing system comprising a network of first nodes adhering to a given consensus protocol at a reconfiguration service. The computer services the network by receiving a request of change of status of a second node with respect to the network. The computer informs at least a subset of the first nodes of the received request. The computer obtains an approval of the request, whereby at least a subset of the first nodes collectively approve the change of status as a result of contributions processed according to the given consensus protocol. The computer updates a configuration log according to request approvals obtained by servicing the network. The computer addresses requests of clients about configurations of the network based on the updated configuration log.

The present disclosure facilitates improving the operation of a cloud service by updating its configuration information and its resource requirements. The resource utilization of the cloud service can be monitored, and a decision logic module can determine whether action is required. When action is required, an update can be prepared and applied, and notifications can be generated about the condition and its resolution. Resolutions can require correlation of multiple cloud services to provide real-time access to information that is not otherwise available to a single entity. Resolutions can be learned and predicted in a number of ways using a predictive engine.