Abstract: One or more computing devices, systems, and/or methods for monitoring levels of activity of client devices using a cluster of servers having a decentralized network architecture are provided, where over-counting, which may be caused by an uneven distribution of requests transmitted by the client devices to the cluster of servers, may be mitigated. For example, a request may be received by a first server, of the cluster of servers, from a client device. A first counter value associated with a level of activity of the client device may be incremented by a first number. One or more data packets may be transmitted to one or more servers of the cluster of servers. Each data packet of the one or more data packets may comprise an instruction to increment a counter value associated with the client device by a second number, which may be different than the first number.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: One or more computing devices, systems, and/or methods for monitoring levels of activity of client devices using a cluster of servers having a decentralized network architecture are provided, where over-counting, which may be caused by an uneven distribution of requests transmitted by the client devices to the cluster of servers, may be mitigated. For example, a request may be received by a first server, of the cluster of servers, from a client device. A first counter value associated with a level of activity of the client device may be incremented by a first number. One or more data packets may be transmitted to one or more servers of the cluster of servers. Each data packet of the one or more data packets may comprise an instruction to increment a counter value associated with the client device by a second number, which may be different than the first number.

Abstract: One or more computing devices, systems, and/or methods for monitoring levels of activity of client devices using a cluster of servers having a decentralized network architecture are provided, where over-counting, which may be caused by an uneven distribution of requests transmitted by the client devices to the cluster of servers, may be mitigated. For example, a request may be received by a first server, of the cluster of servers, from a client device. A first counter value associated with a level of activity of the client device may be incremented by a first number. One or more data packets may be transmitted to one or more servers of the cluster of servers. Each data packet of the one or more data packets may comprise an instruction to increment a counter value associated with the client device by a second number, which may be different than the first number.

Abstract: One or more computing devices, systems, and/or methods for monitoring levels of activity of client devices using a cluster of servers having a decentralized network architecture are provided, where over-counting, which may be caused by an uneven distribution of requests transmitted by the client devices to the cluster of servers, may be mitigated. For example, a request may be received by a first server, of the cluster of servers, from a client device. A first counter value associated with a level of activity of the client device may be incremented by a first number. One or more data packets may be transmitted to one or more servers of the cluster of servers. Each data packet of the one or more data packets may comprise an instruction to increment a counter value associated with the client device by a second number, which may be different than the first number.

Abstract: 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.