Abstract: In some embodiments, a method for managing resources in a data center includes a data center having a plurality of servers in a network. The data center provides a virtual machine for each of a plurality of users, each virtual machine to use a portion of hardware resources of the data center. The hardware resources include storage and processing resources distributed onto each of the plurality of servers. The method further includes sending messages amongst the servers, some of the messages being sent from a server including status information regarding a hardware resource utilization status of that server. The method further includes detecting a request from the virtual machine to handle a workload requiring increased use of the hardware resources, and provisioning the servers to temporarily allocate additional resources to the virtual machine, wherein the provisioning is based on status information provided by one or more of the messages.

Abstract: Systems and methods to manage workloads and hardware resources in a data center or cloud. In one embodiment, a method includes a data center having a plurality of servers in a network. The data center provides a virtual machine for each of a plurality of users, each virtual machine to use a portion of hardware resources of the data center. The hardware resources include storage and processing resources distributed onto each of the plurality of servers. The method further includes sending messages amongst the servers, some of the messages being sent from a server including status information regarding a hardware resource utilization status of that server. The method further includes detecting a request from the virtual machine to handle a workload requiring increased use of the hardware resources, and provisioning the servers to temporarily allocate additional resources to the virtual machine, wherein the provisioning is based on status information provided by one or more of the messages.

Abstract: Systems, methods, and media for transparently optimizing a workload of a containment abstraction are provided herein. Methods may include monitoring a workload of the containment abstraction, the containment abstraction being at least partially hardware bound, the workload corresponding to resource utilization of the containment abstraction, converting the containment abstraction from being at least partially hardware bound to being entirely central processing unit (CPU) bound by placing the containment abstraction in a memory store, based upon the workload, and allocating the workload of the containment abstraction across at least a portion of a data center to optimize the workload of the containment abstraction.

Abstract: Systems, methods, and media for transparently optimizing a workload of a containment abstraction are provided herein. Methods may include monitoring a workload of the containment abstraction, the containment abstraction being at least partially hardware bound, the workload corresponding to resource utilization of the containment abstraction, converting the containment abstraction from being at least partially hardware bound to being entirely central processing unit (CPU) bound by placing the containment abstraction in a memory store, based upon the workload, and allocating the workload of the containment abstraction across at least a portion of a data center to optimize the workload of the containment abstraction.

Abstract: Systems, methods, and media for transparently optimizing a workload of a containment abstraction are provided herein. Methods may include monitoring a workload of the containment abstraction, the containment abstraction being at least partially hardware bound, the workload corresponding to resource utilization of the containment abstraction, converting the containment abstraction from being at least partially hardware bound to being entirely central processing unit (CPU) bound by placing the containment abstraction in a memory store, based upon the workload, and allocating the workload of the containment abstraction across at least a portion of a data center to optimize the workload of the containment abstraction.

Abstract: Systems and methods to manage workloads and hardware resources in a data center or cloud. In one embodiment, a method includes a data center having a plurality of servers in a network. The data center provides a virtual machine for each of a plurality of users, each virtual machine to use a portion of hardware resources of the data center. The hardware resources include storage and processing resources distributed onto each of the plurality of servers. The method further includes sending messages amongst the servers, some of the messages being sent from a server including status information regarding a hardware resource utilization status of that server. The method further includes detecting a request from the virtual machine to handle a workload requiring increased use of the hardware resources, and provisioning the servers to temporarily allocate additional resources to the virtual machine, wherein the provisioning is based on status information provided by one or more of the messages.

Abstract: Systems, methods, and media for transparently optimizing a workload of a containment abstraction are provided herein. Methods may include monitoring a workload of the containment abstraction, the containment abstraction being at least partially hardware bound, the workload corresponding to resource utilization of the containment abstraction, converting the containment abstraction from being at least partially hardware bound to being entirely central processing unit (CPU) bound by placing the containment abstraction in a memory store, based upon the workload, and allocating the workload of the containment abstraction across at least a portion of a data center to optimize the workload of the containment abstraction.

Abstract: Systems and methods for sizing resources in a cloud-based environment are provided. In an exemplary embodiment, a method includes receiving quality of service requirements and a functional description of a cloud architecture associated with the application, including application resources and relations between the application resources, performing latency analysis of data packets in a compute layer of the cloud architecture, with the latency analysis including comparing size per time metrics of the data packets, determining minimal resources to guarantee the quality of service requirements based on the latency analysis and the quality of service requirements, and providing to the data center the minimal resources.

Abstract: Systems and methods to manage workloads and hardware resources in a data center or cloud. In one embodiment, a method includes a data center having a plurality of servers in a network. The data center provides a virtual machine for each of a plurality of users, each virtual machine to use a portion of hardware resources of the data center. The hardware resources include storage and processing resources distributed onto each of the plurality of servers. The method further includes sending messages amongst the servers, some of the messages being sent from a server including status information regarding a hardware resource utilization status of that server. The method further includes detecting a request from the virtual machine to handle a workload requiring increased use of the hardware resources, and provisioning the servers to temporarily allocate additional resources to the virtual machine, wherein the provisioning is based on status information provided by one or more of the messages.

Abstract: Systems and methods to manage workloads and hardware resources in a data center or cloud. In one embodiment, a method includes a data center having a plurality of servers in a network. The data center provides a virtual machine for each of a plurality of users, each virtual machine to use a portion of hardware resources of the data center. The hardware resources include storage and processing resources distributed onto each of the plurality of servers. The method further includes sending messages amongst the servers, some of the messages being sent from a server including status information regarding a hardware resource utilization status of that server. The method further includes detecting a request from the virtual machine to handle a workload requiring increased use of the hardware resources, and provisioning the servers to temporarily allocate additional resources to the virtual machine, wherein the provisioning is based on status information provided by one or more of the messages.

Abstract: Systems and methods to manage workloads and hardware resources in a data center or cloud. In one embodiment, a method includes a data center having a plurality of servers in a network. The data center provides a virtual machine for each of a plurality of users, each virtual machine to use a portion of hardware resources of the data center. The hardware resources include storage and processing resources distributed onto each of the plurality of servers. The method further includes sending messages amongst the servers, some of the messages being sent from a server including status information regarding a hardware resource utilization status of that server. The method further includes detecting a request from the virtual machine to handle a workload requiring increased use of the hardware resources, and provisioning the servers to temporarily allocate additional resources to the virtual machine, wherein the provisioning is based on status information provided by one or more of the messages.

Abstract: A heat exchanger evaluation system (84) includes a refrigeration subsystem (126) and a platform (94) in communication with the subsystem (126) for attachment of a heat exchanger (32). The system, (84) further includes a thermal imaging camera (168) and a monitor (100). A method (180) entails routing a fluid (38) through the heat exchanger (32) via the refrigeration subsystem (126). The camera (168) detects the temperature variation across the heat exchanger (32) as the fluid (38) flows through the heat exchanger, and provides successive thermal images representing the temperature variation responsive to the flow of the fluid (38). The thermal images are utilized to determine an efficacy of the flow through the heat exchanger (32). In particular, a determination can be made as to whether the flow deviates from a pre-determined flow path (79) of the fluid (38) through the heat exchanger.