Abstract: A distributed processing system includes a cloud-based network and a back-end system. The cloud-based network has an orchestrator and a plurality of application pods. Each application pod includes an application and an exporter configured to provide telemetry information for the associated application. The back-end system has an application analysis module that receives the telemetry information from the application pods, determines an interdependency between the applications, determines a scaling between the applications, and directs the orchestrator to launch the applications based on the scaling.

Abstract: In one or more embodiments, one or more systems, one or more methods, and/or one or more processes may determine first thermal attribute values associated with multiple information handling systems (IHSs) with respect to a period of time as the IHSs execute a first workload; determine multiple variance ranges respectively associated with the first thermal attributes; periodically determine second thermal attribute values associated with the IHSs as the IHSs execute a second workload; determine that a thermal attribute value of the second thermal attribute values exceeds a respective variance range of the variance ranges as a first information handling system (IHS) of the IHSs executes the second workload; generate an alert based at least on the thermal attribute value exceeding the respective variance range; and in response to the alert, transfer at least a portion of the second workload from the first IHS to a second IHS of the IHSs.

Abstract: A system, method, and computer-readable medium for optimizing overall edge datacenter power and maintaining a compliant thermal state of edge devices in a cluster. Thermal compliant policy of the edge devices as to lower and upper limits is determined. Telemetry attributes from the edge devices are applied to a machine learning (ML) model to predict thermal condition of the edge devices over time. Workload is offloaded from one edge device to another edge device if predicted thermal condition of one of the edge devices is not within the limits of the thermal compliant policy.

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: 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: 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: An information handling system receives a notification regarding a state of the information handling system, and determines an alert management policy associated with the notification regarding the state of the information handling system. The system also applies an alert management action to enforce the alert management policy.

Abstract: A network (e.g. cloud or enterprise network) includes servers (110) and switches (120) each of which has multiple ports. A bare-metal server's ports are configured for different roles, e.g. management role or data role. The configuration is at least partially automated using a blueprint (340) which does not necessarily specify the roles for the server ports, but may associate a role with a network parameter, e.g. Maximum Transfer Unit (MTU) or QoS. A management computer (320) obtains, from switches, (i) network parameters configured on switch ports, and (ii) MAC addresses for the adjacent server ports. The management computer matches the blueprint's parameters with the switch ports' parameters, and associates matched parameters with the roles specified by the blueprint. These roles are configured on the corresponding server ports. Other features are also provided.

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.

Abstract: A Computing environment is described to enable an information handling system (IHS) to receive a public encryption key from another IHS; and decrypt with a public encryption key one or more encrypted symmetric encryption keys, encrypted via a private encryption key, to obtain one or more symmetric encryption keys respectively associated with one or more memory address ranges. The IHS may physically receive a memory device that was utilized by the other IHS to store information in an encrypted fashion. The IHS may further decrypt, with a first encryption key of the one or more symmetric encryption keys associated with a first address range of the one or more address ranges, first encrypted data stored by the at least one non-volatile memory medium to obtain first data.

Abstract: In one or more embodiments, one or more systems, one or more methods, and/or one or more processes may determine first thermal attribute values associated with multiple information handling systems (IHSs) with respect to a period of time as the IHSs execute a first workload; determine multiple variance ranges respectively associated with the first thermal attributes; periodically determine second thermal attribute values associated with the IHSs as the IHSs execute a second workload; determine that a thermal attribute value of the second thermal attribute values exceeds a respective variance range of the variance ranges as a first information handling system (IHS) of the IHSs executes the second workload; generate an alert based at least on the thermal attribute value exceeding the respective variance range; and in response to the alert, transfer at least a portion of the second workload from the first IHS to a second IHS of the IHSs.

Abstract: In one or more embodiments, one or more systems, one or more methods, and/or one or more processes may: receive performance information for a base workload; determine multiple threshold values of multiple storage media layers of each IHS of a storage cluster based at least on the performance information for the base workload and multiple inventory information respectively associated with multiple storage media layers of each IHS of the storage cluster; receive multiple condition values respectively associated with the multiple storage media layers of an IHS of the storage cluster; determine that a condition value of the multiple condition values associated with a storage media layer of the multiple storage media layers is at or below a threshold value of the multiple threshold values associated with the storage media layer of the multiple storage media layers; and reduce a storage workload of a specific IHS of the storage cluster.

Abstract: In one or more embodiments, an information handling system (IHS) may receive a public encryption key from another IHS; and decrypt with a public encryption key the one or more encrypted symmetric encryption keys, encrypted via a private encryption key, to obtain one or more symmetric encryption keys respectively associated with one or more memory address ranges. The IHS may physically receive a memory device, which includes at least one volatile memory medium and at least one non-volatile memory medium, that was utilized by the other IHS to store information in an encrypted fashion. The IHS may further decrypt with a first encryption key of the one or more symmetric encryption keys associated with a first address range of the one or more address ranges, by the information handling system, first encrypted data stored by the at least one non-volatile memory medium to obtain first data.

Abstract: A network (e.g. cloud or enterprise network) includes servers (110) and switches (120) each of which has multiple ports. A bare-metal server's ports are configured for different roles, e.g. management role or data role. The configuration is at least partially automated using a blueprint (340) which does not necessarily specify the roles for the server ports, but may associate a role with a network parameter, e.g. Maximum Transfer Unit (MTU) or QoS. A management computer (320) obtains, from switches, (i) network parameters configured on switch ports, and (ii) MAC addresses for the adjacent server ports. The management computer matches the blueprint's parameters with the switch ports' parameters, and associates matched parameters with the roles specified by the blueprint. These roles are configured on the corresponding server ports. Other features are also provided.