Abstract: A datacenter includes a datacenter efficiency management system coupled to node devices. For each of the node devices and based on a power consumption associated with that node device and a performance associated with that node device, the datacenter efficiency management system generates a node group ranking that it uses to group subsets of the node devices into respective homogenous node groups, and then deploys a respective workload on at least one node device in each of the homogenous node groups. Based on at least one of a node workload bandwidth, a node power consumption, and a node health of each node device on which a workload was deployed, the datacenter efficiency management system then generates a workload performance efficiency ranking of the node devices that it then uses to migrate at least one workload between the node devices.

Abstract: Back pressure is mapped within a network, and primary bottlenecks are distinguished from dependent bottlenecks. Further, the presently disclosed technology is capable of performing network healing operations designed to reduce the data load on primary bottlenecks while ignoring dependent bottlenecks. Still further, the presently disclosed technology teaches identifying and/or suggesting a switch port for adding a node to the network. More specifically, various implementations analyze traffic load and back pressure in a network, identify primary and dependent bottlenecks, resolve the primary bottlenecks, collect new node parameters, and/or select a switch port for the new node. Further, a command can be sent to a selected switch to activate an indicator on the selected port. New node parameters may include new node type, maximum load, minimum load, time of maximum load, time of minimum load and type of data associated with the new node.

Abstract: Manageability tools are provided for allowing an administrator to have better control over switches in a lossless network of switches. These tools provide the ability to detect slow drain and congestion bottlenecks, detect stuck virtual channels and loss of credits, while hold times on edge ASICs to be different from hold times on core ASICs, and mitigate severe latency bottlenecks.

Abstract: Back pressure is mapped within a network, and primary bottlenecks are distinguished from dependent bottlenecks. Further, the presently disclosed technology is capable of performing network healing operations designed to reduce the data load on primary bottlenecks while ignoring dependent bottlenecks. Still further, the presently disclosed technology teaches identifying and/or suggesting a switch port for adding a node to the network. More specifically, various implementations analyze traffic load and back pressure in a network, identify primary and dependent bottlenecks, resolve the primary bottlenecks, collect new node parameters, and/or select a switch port for the new node. Further, a command can be sent to a selected switch to activate an indicator on the selected port. New node parameters may include new node type, maximum load, minimum load, time of maximum load, time of minimum load and type of data associated with the new node.

Abstract: Back pressure is mapped within a network, and primary bottlenecks are distinguished from dependent bottlenecks. Further, the presently disclosed technology is capable of performing network healing operations designed to reduce the data load on primary bottlenecks while ignoring dependent bottlenecks. Still further, the presently disclosed technology teaches identifying and/or suggesting a switch port for adding a node to the network. More specifically, various implementations analyze traffic load and back pressure in a network, identify primary and dependent bottlenecks, resolve the primary bottlenecks, collect new node parameters, and/or select a switch port for the new node. Further, a command can be sent to a selected switch to activate an indicator on the selected port. New node parameters may include new node type, maximum load, minimum load, time of maximum load, time of minimum load and type of data associated with the new node.

Abstract: Manageability tools are provided for allowing an administrator to have better control over switches in a lossless network of switches. These tools provide the ability to detect slow drain and congestion bottlenecks, detect stuck virtual channels and loss of credits, configure hold times on edge switches to be different from hold times on core switches, and mitigate severe latency bottlenecks.

Abstract: Manageability tools are provided for allowing an administrator to have better control over switches in a lossless network of switches. These tools provide the ability to detect slow drain and congestion bottlenecks, detect stuck virtual channels and loss of credits, while hold times on edge ASICs to be different from hold times encore ASICs, and mitigate severe latency bottlenecks.

Abstract: Manageability tools are provided for allowing an administrator to have better control over switches in a lossless network of switches. These tools provide the ability to detect slow drain and congestion bottlenecks, detect stuck virtual channels and loss of credits, while hold times on edge ASICs to be different from hold times on core ASICs, and mitigate severe latency bottlenecks.

Abstract: Manageability tools are provided for allowing an administrator to have better control over switches in a lossless network of switches. These tools provide the ability to detect slow drain and congestion bottlenecks, detect stuck virtual channels and loss of credits, configure hold times on edge switches to be different from hold times on core switches, and mitigate severe latency bottlenecks.

Abstract: Manageability tools are provided for allowing an administrator to have better control over switches in a lossless network of switches. These tools provide the ability to detect slow drain and congestion bottlenecks, detect stuck virtual channels and loss of credits, while hold times on edge ASICs to be different from hold times on core ASICs, and mitigate severe latency bottlenecks.

Abstract: One embodiment of the present invention provides a system that facilitates traffic management in a network. During operation, the system detects a bottleneck in a network based on network-state information received from one or more switches. The system further identifies a data flow that contributes to the bottleneck and generates a signal to reduce the data flow from the data flow's source device.

Abstract: Manageability tools are provided for allowing an administrator to have better control over switches in a lossless network of switches. These tools provide the ability to detect slow drain and congestion bottlenecks, detect stuck virtual channels and loss of credits, configure hold times on edge ASICs to be different from hold times on core ASICs, and mitigate severe latency bottlenecks.

Abstract: Manageability tools are provided for allowing an administrator to have better control over switches in a lossless network of switches. These tools provide the ability to detect slow drain and congestion bottlenecks, detect stuck virtual channels and loss of credits, while hold times on edge ASICs to be different from hold times encore ASICs, and mitigate severe latency bottlenecks.

Abstract: Manageability tools are provided for allowing an administrator to have better control over switches in a lossless network of switches. These tools provide the ability to detect slow drain and congestion bottlenecks, detect stuck virtual channels and loss of credits, while hold times on edge ASICs to be different from hold times encore ASICs, and mitigate severe latency bottlenecks.

Abstract: Manageability tools are provided for allowing an administrator to have better control over switches in a lossless network of switches. These tools provide the ability to detect slow drain and congestion bottlenecks, detect stuck virtual channels and loss of credits, while hold times on edge ASICs to be different from hold times encore ASICs, and mitigate severe latency bottlenecks.

Abstract: Manageability tools are provided for allowing an administrator to have better control over switches in a lossless network of switches. These tools provide the ability to detect slow drain and congestion bottlenecks, detect stuck virtual channels and loss of credits, while hold times on edge ASICs to be different from hold times encore ASICs, and mitigate severe latency bottlenecks.

Abstract: Manageability tools are provided for allowing an administrator to have better control over switches in a lossless network of switches. These tools provide the ability to detect slow drain and congestion bottlenecks, detect stuck virtual channels and loss of credits, while hold times on edge ASICs to be different from hold times encore ASICs, and mitigate severe latency bottlenecks.

Abstract: Back pressure is mapped within a network, and primary bottlenecks are distinguished from dependent bottlenecks. Further, the presently disclosed technology is capable of performing network healing operations designed to reduce the data load on primary bottlenecks while ignoring dependent bottlenecks. Still further, the presently disclosed technology teaches identifying and/or suggesting a switch port for adding a node to the network. More specifically, various implementations analyze traffic load and back pressure in a network, identify primary and dependent bottlenecks, resolve the primary bottlenecks, collect new node parameters, and/or select a switch port for the new node. Further, a command can be sent to a selected switch to activate an indicator on the selected port. New node parameters may include new node type, maximum load, minimum load, time of maximum load, time of minimum load and type of data associated with the new node.

Abstract: Back pressure is mapped within a network, and primary bottlenecks are distinguished from dependent bottlenecks. Further, the presently disclosed technology is capable of performing network healing operations designed to reduce the data load on primary bottlenecks while ignoring dependent bottlenecks. Still further, the presently disclosed technology teaches identifying and/or suggesting a switch port for adding a node to the network. More specifically, various implementations analyze traffic load and back pressure in a network, identify primary and dependent bottlenecks, resolve the primary bottlenecks, collect new node parameters, and/or select a switch port for the new node. Further, a command can be sent to a selected switch to activate an indicator on the selected port. New node parameters may include new node type, maximum load, minimum load, time of maximum load, time of minimum load and type of data associated with the new node.

Abstract: Back pressure is mapped within a network, and primary bottlenecks are distinguished from dependent bottlenecks. Further, the presently disclosed technology is capable of performing network healing operations designed to reduce the data load on primary bottlenecks while ignoring dependent bottlenecks. Still further, the presently disclosed technology teaches identifying and/or suggesting a switch port for adding a node to the network. More specifically, various implementations analyze traffic load and back pressure in a network, identify primary and dependent bottlenecks, resolve the primary bottlenecks, collect new node parameters, and/or select a switch port for the new node. Further, a command can be sent to a selected switch to activate an indicator on the selected port. New node parameters may include new node type, maximum load, minimum load, time of maximum load, time of minimum load and type of data associated with the new node.