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.

Disclosed herein are systems, devices, and methods for providing auto-scaling in a cluster of device instances. In one embodiment, a method is disclosed comprising updating, using a distributed counter, a metric associated with one or more instances executing a network application; identifying that the metric has exceeded a threshold defined in a scaling policy based on comparing the distributed counter to the scaling policy; identifying a command to execute in response to the metric exceeding the threshold; and executing the command to modify the one or more instances.

A method by a computing device for dynamically configuring a network comprising a plurality of computing devices configured to perform training of a machine learning model is provided. The method includes dynamically identifying a change in a state of a leader computing device, wherein the leader computing device includes one of a server computing device and a client computing device and wherein the plurality of computing devices include server computing devices and/or client computing devices. The method further includes determining whether the change in the state triggers a new leader computing device to be selected. The method further includes initiating a new leader election among the plurality of computing devices responsive to determining the change in the state triggers the new leader computing device to be selected. The method further includes receiving an identification of the new leader computing device based on the initiating of the new leader election.

An asynchronous state machine replication solution in a system of replicas includes executing multiple instances of a consensus protocol, referred to as leader-based views (LBVs) in each replica, where each replica is a leader participant in one of the LBV instances. Each replica drives a decision based on the consensus being reached among the LBV instances, rather than relying the expiration of timers and view changes to drive progress.

Autonomous management of resources by an administrative node network is disclosed, including: receiving, at a first node of a plurality of nodes associated with an administrative node network, a resource request directed to the administrative node network, wherein the administrative node network is associated with managing a set of resources; obtaining a first proposal with respect to the resource request; obtaining a second proposal with respect to the resource request from a second node of the plurality of nodes associated with the administrative node network; and determining a processing consensus associated with the resource request based at least in part on the first proposal and the second proposal.

This disclosure provides systems, methods and apparatus, including computer programs encoded on computer storage media, for an internet of things (IoT) device. In some implementations, the IoT device can select an operating role for the first IoT device in a local network. The operating role may be selected from between an endpoint role and a relay role. The operating role may be dynamically selected by the first IoT device based whether the relay role would enhance connectivity for a client device that is within a wireless range of the first IoT device. The IoT device may participate in a self-organizing network (SON) and may coordinate with other devices in the SON to enhance wireless coverage for the client device based on a position of the client device relative to the one or more IoT devices.

Various approaches for providing network maintenance and health monitoring. In some cases, some approaches include systems, methods, and/or devices that provide for receiving and cataloging network incidents and invoking automated remediation in relation to network incidents.

Techniques are disclosed for identifying faulty links in a virtualized computing environment. Network path latency information is received for one or more network paths in the networked computing environment. Based on the network path latency information, a probable presence of a faulty component is determined. In response to the determination, physical links for a network path associated with the probable faulty component are identified. Information indicative of likely sources of the probable faulty component is received from multiple hosts of the networked computing environment. Based on the identified physical links and information, a faulty component is determined.

Determining if a new federation should be formed. A method includes a voter node determining that it has sufficient votes to form a new federation. The method further includes determining that no node existing in a previous federation already has a quorum of valid global tickets. Each global ticket indicates that a node agrees that a federation should continue to exist. As a result, the voter node forms a new federation.

Systems, apparatus and methods are disclosed which are directed to computer program products for automatically understanding and addressing the QoS adherence of a workload in a computer network. The use of pricing can be used to provide QoS adherence for any type of demand or service. The disclosed methodologies can be applied to applications, to virtual machines, to storage, and/or other types of workload, demand or service that is achieved through the use of shared resources.