In one embodiment, a label stability analyzer service receives classification data indicative of device type labels assigned to endpoints in a network by a device classification service. The label stability analyzer service counts device type label changes made by the device classification service to the endpoints. The label stability analyzer service computes variability metrics for the device type labels, wherein the variability metric for a device type label is based on a count of the device type label changes associated with that label. The label stability analyzer service determines, based on one of the variability metrics for a particular one of the device type labels exceeding a threshold value, a configuration change for the device classification service that adjusts how the device classification service applies the particular label to endpoints. The label stability analyzer service provides the configuration change to the device classification service.

In one embodiment, a label stability analyzer service receives classification data indicative of device type labels assigned to endpoints in a network by a device classification service. The label stability analyzer service counts device type label changes made by the device classification service to the endpoints. The label stability analyzer service computes variability metrics for the device type labels, wherein the variability metric for a device type label is based on a count of the device type label changes associated with that label. The label stability analyzer service determines, based on one of the variability metrics for a particular one of the device type labels exceeding a threshold value, a configuration change for the device classification service that adjusts how the device classification service applies the particular label to endpoints. The label stability analyzer service provides the configuration change to the device classification service.

[Object] Effectively perform data communication [Solving Means] A communication device includes: a LINK that generates a first output signal on a basis of a first external signal from a first external device, outputs the first output signal to a second external device, generates a second output signal on a basis of a second external signal from the second external device, and outputs the second output signal to the first external device, in which each of the first output signal and the second external signal includes command information indicating content of a command transmitted from the first external device, final-destination-device-identification-information for identifying a final destination device of data transmitted from the first external device, internal address information indicating an internal address of the final destination device, data length information indicating a length of the data transmitted from the first external device, and data-end-position-information indicating an end position of the data transmitted from the first external device.

A networking system may include a switch coupled to a computing resource. A resource management system may control the computing resource. A controller may be coupled to the switch. The controller may include a resource management interface that is coupled to the resource management system via a communications link. The resource management interface may receive computing resource information for the computing resource via the communications link. The controller may provide control data to the switch to update a cloud network for the computing resource based on the received computing resource information.

The invention enables high-availability, high-scale, high security and disaster recovery for API computing, including in terms of capture of data traffic passing through proxies, routing communications between clients and servers, and load balancing and/or forwarding functions. The invention inter alia provides (i) a scalable cluster of proxies configured to route communications between clients and servers, without any single point of failure, (ii) proxy nodes configured for implementing the scalable cluster (iii) efficient methods of configuring the proxy cluster, (iv) natural resiliency of clusters and/or proxy nodes within a cluster, (v) methods for scaling of clusters, (vi) configurability of clusters to span multiple servers, multiple racks and multiple datacenters, thereby ensuring high availability and disaster recovery (vii) switching between proxies or between servers without loss of session.

The invention enables high-availability, high-scale, high security and disaster recovery for API computing, including in terms of capture of data traffic passing through proxies, routing communications between clients and servers, and load balancing and/or forwarding functions. The invention inter alia provides (i) a scalable cluster of proxies configured to route communications between clients and servers, without any single point of failure, (ii) proxy nodes configured for implementing the scalable cluster (iii) efficient methods of configuring the proxy cluster, (iv) natural resiliency of clusters and/or proxy nodes within a cluster, (v) methods for scaling of clusters, (vi) configurability of clusters to span multiple servers, multiple racks and multiple datacenters, thereby ensuring high availability and disaster recovery (vii) switching between proxies or between servers without loss of session.

A computer network optimization methodology is disclosed. In a computer-implemented method, components of a computing environment are automatically monitored, and have a feature selection analysis performed thereon. Provided the feature selection analysis determines that features of the components are in frequent communication and generating network latency. Provided the feature selection analysis determines that features of the components are not well defined, a similarity analysis of the features is performed. Results of the feature selection methodology are generated, and the components involved in the network traffic latency are reassigned to migrate the latency.

A computer network optimization methodology is disclosed. In a computer-implemented method, components of a computing environment are automatically monitored, and have a feature selection analysis performed thereon. Provided the feature selection analysis determines that features of the components are in frequent communication and generating network latency. Provided the feature selection analysis determines that features of the components are not well defined, a similarity analysis of the features is performed. Results of the feature selection methodology are generated, and the components involved in the network traffic latency are reassigned to migrate the latency.

Systems, computer-readable media, and methods are disclosed for parallel data processing for service function chains with network functions spanning multiple servers. An example system includes a first server hosting a first network function of a service function chain, a second server hosting a second network function of the service function chain, a mirror function deployed in a first switch to replicate a plurality of packets received by the system and to send respective copies of the plurality of packets to the first network function and to at least one of the second network function and a third network function of the service function chain, and a merge function deployed in a second switch to merge respective outputs of the first network function and the at least one of the second network function and the third network function.

Systems, computer-readable media, and methods are disclosed for parallel data processing for service function chains with network functions spanning multiple servers. An example system includes a first server hosting a first network function of a service function chain, a second server hosting a second network function of the service function chain, a mirror function deployed in a first switch to replicate a plurality of packets received by the system and to send respective copies of the plurality of packets to the first network function and to at least one of the second network function and a third network function of the service function chain, and a merge function deployed in a second switch to merge respective outputs of the first network function and the at least one of the second network function and the third network function.