Abstract: Managing power consumption for computing cluster, including for each IHS of the computing cluster: executing I/O computing workloads at the IHS associated with movement of block storage data, stored at a disk array in communication with the IHS, between the disk array and the IHS; during execution of the I/O computing workloads, determining an I/O power usage of the IHS; calculating an accumulated I/O power consumption of the plurality of IHS based on a summation of the I/O power usage of each of the IHS; during movement of the block storage data, calculating a power consumption of the disk array; calculating, for each IHS, a power storage consumption of the IHS based on the I/O power usage of the IHS, the accumulated I/O power consumption, and the power consumption of the disk array; allocating additional workloads among the plurality of IHS based on the power storage consumption of each IHS.

Abstract: Technology described herein relates to management of operational execution by one or more plugins, services and/or consoles of a computing system. A method can comprise registering, by a conflict resolution manager (CRM) controller of a system, a subset of control components of a set of control components of the system, wherein the registering comprises logging operation capabilities of the subset of control components, ranking, by the CRM controller, respective control components of the subset, wherein the ranking is performed based on an operation comprised by the operation capabilities, and generating, by the CRM controller, a permission for performance of the operation by a selected control component of the subset having a highest rank determined by the ranking. The control components can comprise a plugin of, or to be installed at, at least one of the system or a management console of the system, which can be a computing system.

Abstract: Managing computing workloads within a computing environment including identifying computing parameters of datacenter elements of each computing cluster of a computing environment; for each computing cluster of the computing environment: determining a health of the power device of the computing cluster; for each computing node of the computing cluster: determining a processing load of the computing node; determining a computing cost associated with a geo-location of the computing node; calculating, for each computing cluster, an availability of computing resources of the computing cluster based on the computing parameters of the data center elements of the computing cluster, the health of the power device of the computing cluster, the processing load of each computing node of the computing cluster, and the computing cost of each computing node of the computing cluster; generating a ranking of each computing cluster based on the availability of the computing resources of the computing cluster.

Abstract: Described herein are methods and a system for reading and reporting of energy consumption data of managed hardware, such as devices in a data center, and scope 2 GHG emissions attributable to the use of the devices. Emission factors are captured which are associated with energy sources that provide energy to the data center and the devices. Energy consumption of the devices are read. The consumed energy of the devices is converted to GHG emissions and reported.

Abstract: Managing power consumption for computing cluster, including for each IHS of the computing cluster: executing I/O computing workloads at the IHS associated with movement of block storage data, stored at a disk array in communication with the IHS, between the disk array and the IHS; during execution of the I/O computing workloads, determining an I/O power usage of the IHS; calculating an accumulated I/O power consumption of the plurality of IHS based on a summation of the I/O power usage of each of the IHS; during movement of the block storage data, calculating a power consumption of the disk array; calculating, for each IHS, a power storage consumption of the IHS based on the I/O power usage of the IHS, the accumulated I/O power consumption, and the power consumption of the disk array; allocating additional workloads among the plurality of IHS based on the power storage consumption of each IHS.

Abstract: Technology described herein relates to dynamic adjustment of power capping for one or more servers of a subset of servers. A method can comprise generating, by a system operatively coupled to a processor, for a first server subset of a server system, weighted average values comprising a first weighted average value of current workload priority at the first server subset, a second weighted average value of current performance efficiency of the first server subset, and a third weighted average value of predicted future power usage for the first server subset, ranking, by the system, the first server subset as compared to a second server subset of the server system that does not overlap servers with the first server subset, wherein the ranking is based on at least one of the weighted average values, and applying, by the system, a power cap to the first server subset based on the ranking.

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: An information handling system may include at least one processor and a memory coupled to the at least one processor. The information handling system may be configured to: receive configuration data from a managed information handling system; receive compatibility data from a vendor of the managed information handling system; determine, based on the configuration data and the compatibility data, that the managed information handling system has drifted from a predetermined configuration; and based on the determination of drift, execute a responsive action with regard to the managed information handling system.

Abstract: A cooling-power-consumption-based workload allocation system includes a workload allocation system coupled to at least one client device and a plurality of server devices. The workload allocation system receives a first workload request that identifies a first workload from the at least one client device, and determines a first workload priority of the first workload relative to a second workload priority of each second workload being performed by the plurality of server devices. Based on the first workload priority of the first workload relative to the second workload priority of each second workload and a cooling-power-utilization-efficiency ranking of each of the plurality of server devices, the workload allocation system identifies a first server device included in the plurality of server devices for performing the first workload, and causes the first server device to perform the first workload.

Abstract: The described technology is generally directed towards a system and method to distribute available power to devices in a group. A group of devices, such as a rack of servers in a data center, can have a group power consumption limit, such as the limit of a power distribution unit that supplies power to the group. The group of devices can each report their individual power consumption to a manager, and the manager can combine the individual power consumptions. The manager can compare the combined power consumption of the group to the group power consumption limit to determine a power headroom. The manager can determine power consumption limits for the devices of the group based on the power headroom, the individual power consumptions, and device priority information.

Abstract: Software-defined fail-safe power draw control is provided for rack power distribution units (PDUs). A PDU power manager can be used to map devices to a PDU and its sockets. The PDU power manager can also identify the power rating of the PDU and its sockets. With this information, the PDU power manager can generate and apply priority-based and dynamic power caps to the devices connected to the PDU. In this way, the PDU power manager can ensure that the power ratings of the PDU and of each of its sockets are not exceeded while ensuring that power delivery is prioritized based on the workloads that the devices may experience.

Abstract: A networked system includes a computing device having a central processing system and accelerator system(s). A central processor/accelerator power management system coupled to the computing device via a network operates to deploy workload(s) on the computing device and receive workload performance information from the computing device that identifies a central processing system utilization of the central processing system in performing the workload(s) and an accelerator system utilization of each accelerator system in performing the workload(s). Based on the workload performance information, the computing device determines a first power consumption ratio of the central processing system and the accelerator system(s) in performing the workload(s), and modifies operation of at least one of the central processing system and the accelerator system(s) to change the first power consumption ratio to a second power consumption ratio that is more power efficient than the first power consumption ratio.

Abstract: The described technology is generally directed towards reallocating power to devices in a group, such as a rack of servers in a datacenter, when no power headroom remains available. Respective devices, which are classified into respective classes corresponding to respective priority device class levels, have power distributed thereto. Upon determining that available power headroom for power capacity distribution among the group of devices has reached an available power capacity distribution lower limit (e.g., zero), reallocation is performed by increasing power capacity allocated to a first device of a higher priority level class, and decreasing power capacity allocated to a second device of a lower priority level class. For more classes, such as high, medium and low, the power can be decreased among the lower priority level classes by a defined ratio, e.g., two-to-one between the medium and low priority classes.

Abstract: The described technology is generally directed towards a system and method to distribute available power to devices in a group. A group of devices, such as a rack of servers in a data center, can have a group power consumption limit, such as the limit of a power distribution unit that supplies power to the group. The group of devices can each report their individual power consumption to a manager, and the manager can combine the individual power consumptions. The manager can compare the combined power consumption of the group to the group power consumption limit to determine a power headroom. The manager can determine power consumption limits for the devices of the group based on the power headroom, the individual power consumptions, and device priority information.

Abstract: A method for managing power in an information handling system (IHS) environment includes initiating, by a power management console, an end to an emergency power reduction protocol on the IHS environment, based on the end to the emergency power reduction protocol, selecting a device priority group, wherein: the device priority group comprises a plurality of IHS devices, and the device priority group is selected based on a priority of the device priority group, obtaining a power usage estimation for the device priority group, and applying a power limit to the device priority group based on available power to the IHS environment and the power usage estimation.

Abstract: A networked system includes a computing device having a central processing system and accelerator system(s). A central processor/accelerator power management system coupled to the computing device via a network operates to deploy workload(s) on the computing device and receive workload performance information from the computing device that identifies a central processing system utilization of the central processing system in performing the workload(s) and an accelerator system utilization of each accelerator system in performing the workload(s). Based on the workload performance information, the computing device determines a first power consumption ratio of the central processing system and the accelerator system(s) in performing the workload(s), and modifies operation of at least one of the central processing system and the accelerator system(s) to change the first power consumption ratio to a second power consumption ratio that is more power efficient than the first power consumption ratio.

Abstract: A datacenter includes a heterogeneous node group efficiency management system that is coupled to node devices and that, based on a power consumption and performance associated with each node device, generates node group rankings that it uses to group subsets of the node devices into respective heterogeneous node groups. The heterogeneous node group efficiency management system then identifies workload characteristic(s) and performance requirement(s) for a workload provided for deployment, identifies a first heterogeneous node group that satisfies the performance requirement for the workload, and identifies first node device(s) that are included in the first heterogeneous node group and that are configured to perform the first workload having the workload characteristic(s) with a higher power efficiency than second node device(s) that are included in the first heterogeneous node group.

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: A method for managing power in an information handling system (IHS) environment includes initiating, by a power management console, an end to an emergency power reduction protocol on the IHS environment, based on the end to the emergency power reduction protocol, selecting a device priority group, wherein: the device priority group comprises a plurality of IHS devices, and the device priority group is selected based on a priority of the device priority group, obtaining a power usage estimation for the device priority group, and applying a power limit to the device priority group based on available power to the IHS environment and the power usage estimation.

Abstract: In one or more embodiments, one or more systems, one or more methods, and/or one or more processes may: monitor, by a management console, power consumption of a virtual machine (VM) executed by a first hypervisor on a first physical information handling system (IHS); migrate, by the management console, the VM from the first hypervisor to a second hypervisor on a second physical IHS; provide, by the first hypervisor, VM migration information to the management console; determine, by the management console, if the second hypervisor has been discovered based at least on the VM migration information; if so, refresh a hypervisor inventory to include identification information associated with the second hypervisor; if not, discover the second hypervisor; detect the VM; associate the VM with the second hypervisor; and monitor, by the management console, the power consumption of the VM executed by the second hypervisor on the second physical IHS.