Abstract: Described herein are systems, methods, and software to manage the assignment of virtual machines to non-uniform memory access (NUMA) nodes of a computing environment. In one implementation, a management service identifies one or more virtual machines in a computing environment with potential NUMA resource issues. The management service further selects a virtual machine from the one or more virtual machines and determines whether a NUMA node associated with the virtual machine satisfies criteria to migrate at least one virtual machine from the NUMA node. If the criteria are satisfied, the management service migrates at least one virtual machine from the NUMA node to a second NUMA node.

Abstract: Described herein are systems, methods, and software to manage power consumption in a software build environment. In one implementation, a monitoring service monitors power consumption information associated with a build environment for one or more software components. The monitoring service further identifies one or more trends associated with the power consumption information based at least on the power consumption information satisfying one or more criteria and generates a summary for display that indicates at least the one or more trends. The monitoring service may also identify and display as part of the summary one or more suggestions to improve power consumption based on the one or more trends.

Abstract: A power optimization system may include a cloud management server coupled to a plurality of clusters via a network, a resource management module residing in the cloud management server, and a cloud power optimizer module residing in the resource management module. Each cluster may include a plurality of physical hosts with at least one virtual machine (VM) running on each physical host. During operation, the cloud power optimizer module may determine background and active power usages of each physical host in the plurality of clusters. Further, the cloud power optimizer module may determine power usage of each VM based on the determined background and active power usages of each physical host. Furthermore, the cloud power optimizer module may continuously balance a distribution of workload on the plurality of physical hosts based on the determined power usage of each VM.

Abstract: Described herein are systems, methods, and software to manage power consumption in a software build environment. In one implementation, a monitoring service monitors power consumption information associated with a build environment for one or more software components. The monitoring service further identifies one or more trends associated with the power consumption information based at least on the power consumption information satisfying one or more criteria and generates a summary for display that indicates at least the one or more trends. The monitoring service may also identify and display as part of the summary one or more suggestions to improve power consumption based on the one or more trends.

Abstract: A system and method for performing an operational metric analysis for a virtual appliance uses application operational data from multiple instances of the virtual appliance. The application operational data is then used to generate an operational metric prediction for the virtual appliance.

Abstract: Techniques for representative-based approach to store historical resource usage data are disclosed. In one embodiment, a management node may include a statistical representative computational unit to obtain historical resource usage data associated with a workload running on a host, divide the historical resource usage data into a plurality of pools with each pool comprising a predefined number of resource usage statistics, and determine a statistical representative corresponding to each of the pools. Each statistical representative may represent the predefined number of resource usage statistics in a corresponding one of the pools. Further, the management node may include a monitoring and managing unit to monitor and/or manage the workload using the statistical representatives.

Abstract: A system and method for performing an operational metric analysis for a virtual appliance uses application operational data from multiple instances of the virtual appliance. The application operational data is then used to generate an operational metric prediction for the virtual appliance.

Abstract: Techniques for representative-based approach to store historical resource usage data are disclosed. In one embodiment, a management node may include a statistical representative computational unit to obtain historical resource usage data associated with a workload running on a host, divide the historical resource usage data into a plurality of pools with each pool comprising a predefined number of resource usage statistics, and determine a statistical representative corresponding to each of the pools. Each statistical representative may represent the predefined number of resource usage statistics in a corresponding one of the pools. Further, the management node may include a monitoring and managing unit to monitor and/or manage the workload using the statistical representatives.

Abstract: A system and method for performing an operational metric analysis for a virtual appliance uses application operational data from multiple instances of the virtual appliance. The application operational data is then used to generate an operational metric prediction for the virtual appliance.

Abstract: A management server and method for load balancing a cluster of host computers analyzes load metrics of clients naming on the host computers in the cluster to select a first client that can be migrated from a first host computer in the cluster to a second host computer in the cluster to improve load balance for the cluster and a second client running on the second host computer that can be swapped with the first client running on the first host computer for a client swapping operation. The client swapping operation involves simultaneously migrating the first client from the first host computer to the second host computer and migrating the second client from the second host computer to the first host computer.

Abstract: A management server and method for load balancing a cluster of host computers analyzes load metrics of clients naming on the host computers in the cluster to select a first client that can be migrated from a first host computer in the cluster to a second host computer in the cluster to improve load balance for the cluster and a second client running on the second host computer that can be swapped with the first client running on the first host computer for a client swapping operation. The client swapping operation involves simultaneously migrating the first client from the first host computer to the second host computer and migrating the second client from the second host computer to the first host computer.

Abstract: A system and method for performing an operational metric analysis for a virtual appliance uses application operational data from multiple instances of the virtual appliance. The application operational data is then used to generate an operational metric prediction for the virtual appliance.