Abstract: Disclosed herein are methods and systems for workload and defect management. According to an aspect, a method includes communicating, to a first computing device, an identifier associated with a second computing device. The method also includes receiving, from the first computing device, maintenance information associated with the identifier. Further, the method also includes implementing a workload management policy at the second computing device based on the maintenance information.

Abstract: In accordance with one or more embodiments of the present invention, methods and systems disclosed herein provide for storage disk file and defect management. According to an aspect, a method includes communicating, to a first computing device, an identifier associated with a storage device. The method also includes receiving, from the first computing device, maintenance information associated with the identifier. Further, the method also includes implementing a storage disk file management policy at the storage device based on the maintenance information. Maintenance or defect information may be provided, for example, for a disk subsystem comprised within a storage device. A disk subsystem with an identified potential defect, even though potential defect is latent, creates a risk to the software workloads running on the IT resource and a potential hazard in a datacenter.

Abstract: Disclosed herein are methods and systems for workload and defect management. According to an aspect, a method includes communicating, to a first computing device, an identifier associated with a second computing device. The method also includes receiving, from the first computing device, maintenance information associated with the identifier. Further, the method also includes implementing a workload management policy at the second computing device based on the maintenance information.

Abstract: Disclosed herein are methods and systems for workload and defect management. According to an aspect, a method includes communicating, to a first computing device, an identifier associated with a second computing device. The method also includes receiving, from the first computing device, maintenance information associated with the identifier. Further, the method also includes implementing a workload management policy at the second computing device based on the maintenance information.

Abstract: Disclosed herein are methods, systems, and computer program products for the placement of a virtual machine within a plurality of cache-coherent NUMA servers. According to an aspect, an example method includes determining a resource requirement of the virtual machine. The example method may also include determining a resource availability of one or more nodes of the plurality of servers. Further, the example method may include selecting placement of the virtual machine within one or more nodes of the plurality of cache-coherent NUMA servers based on the determined resource requirement and the determined resource availability.

Abstract: Virtual machines having a high amount of identical memory pages are grouped under a common hypervisor to enable greater memory savings as the result of transparent page sharing. One method comprises analyzing the software image content of a plurality of virtual machines running on a plurality of hypervisors in a common migration domain, identifying two or more of the virtual machines having greater than a threshold amount of common memory pages, placing the two or more virtual machines under a common hypervisor, and sharing the common memory pages among the two or more virtual machines. Optionally, the identifying of two or more of the virtual machines may include identifying two or more of the virtual machines having the same software image content classifications; thereby, identifying images with a greater affinity for common memory pages.

Abstract: Virtual machines having a high amount of identical memory pages are grouped under a common hypervisor to enable greater memory savings as the result of transparent page sharing. One embodiment provides a computer program product including computer usable program code for performing a method that comprises analyzing the software image content of a plurality of virtual machines running on a plurality of hypervisors in a common migration domain, identifying two or more of the virtual machines having greater than a threshold amount of common memory pages, placing the two or more virtual machines under a common hypervisor, and sharing the common memory pages among the two or more virtual machines. Optionally, the identifying of two or more of the virtual machines may include identifying two or more of the virtual machines having the same software image content classifications; thereby, identifying images with a greater affinity for common memory pages.

Abstract: A computer-implemented method comprises obtaining a cache hit ratio for each of a plurality of virtual machines, and identifying, from among the plurality of virtual machines, a first virtual machine having a cache hit ratio that is less than a threshold ratio. The identified first virtual machine is then migrated from the first physical server having a first cache size to a second physical server having a second cache size that is greater than the first cache size. Optionally, a virtual machine having a cache hit ratio that is less than a threshold ratio is identified on a class-specific basis, such as for L1 cache, L2 cache and L3 cache.

Abstract: A computer implemented method is provided, including monitoring the utilization of resources available within a compute node, wherein the resources include an input/output capacity, a processor capacity, and a memory capacity. The method further comprises allocating virtual machines to the compute node to maximize use of a first one of the resources; and then allocating an additional virtual machine to the compute node to increase the utilization of the resources other than the first one of the resources without over-allocating the first one of the resources. In a web server, the input/output capacity may be the resource to be maximized. However, unused memory capacity and/or processor capacity of the compute node may be used more effectively by identifying an additional virtual machine that is memory intensive or processor intensive to be allocated or migrated to the compute node.

Abstract: Disclosed herein are methods, systems, and computer program products for the placement of a virtual machine within a plurality of cache-coherent NUMA servers. According to an aspect, an example method includes determining a resource requirement of the virtual machine. The example method may also include determining a resource availability of one or more nodes of the plurality of servers. Further, the example method may include selecting placement of the virtual machine within one or more nodes of the plurality of cache-coherent NUMA servers based on the determined resource requirement and the determined resource availability.

Abstract: A computer implemented method is provided, including monitoring network traffic among virtual machines allocated to a plurality of compute nodes on a network, and identifying first and second virtual machines having inter-virtual machine communication over the network in an amount that is greater than a threshold amount of the network traffic. The method further comprises migrating at least one of the first and second virtual machines so that the first and second virtual machines are allocated to the same compute node and the inter-virtual machine communication between the first and second virtual machines is no longer directed over the network. In one embodiment, each compute node is coupled to an Ethernet link of a network switch, and data is obtained from a management information database of the network switch to determine the amount of network bandwidth that is being utilized for communication between the first and second virtual machines.

Abstract: Virtual machines having a high amount of identical memory pages are grouped under a common hypervisor to enable greater memory savings as the result of transparent page sharing. One method comprises analyzing the software image content of a plurality of virtual machines running on a plurality of hypervisors in a common migration domain, identifying two or more of the virtual machines having greater than a threshold amount of common memory pages, placing the two or more virtual machines under a common hypervisor, and sharing the common memory pages among the two or more virtual machines. Optionally, the identifying of two or more of the virtual machines may include identifying two or more of the virtual machines having the same software image content classifications; thereby, identifying images with a greater affinity for common memory pages.

Abstract: Virtual machines having a high amount of identical memory pages are grouped under a common hypervisor to enable greater memory savings as the result of transparent page sharing. One embodiment provides a computer program product including computer usable program code for performing a method that comprises analyzing the software image content of a plurality of virtual machines running on a plurality of hypervisors in a common migration domain, identifying two or more of the virtual machines having greater than a threshold amount of common memory pages, placing the two or more virtual machines under a common hypervisor, and sharing the common memory pages among the two or more virtual machines. Optionally, the identifying of two or more of the virtual machines may include identifying two or more of the virtual machines having the same software image content classifications; thereby, identifying images with a greater affinity for common memory pages.

Abstract: A computer-implemented method comprises obtaining a cache hit ratio for each of a plurality of virtual machines, and identifying, from among the plurality of virtual machines, a first virtual machine having a cache hit ratio that is less than a threshold ratio. The identified first virtual machine is then migrated from the first physical server having a first cache size to a second physical server having a second cache size that is greater than the first cache size. Optionally, a virtual machine having a cache hit ratio that is less than a threshold ratio is identified on a class-specific basis, such as for L1 cache, L2 cache and L3 cache.

Abstract: A computer implemented method is provided, including monitoring network traffic among virtual machines that are allocated to a plurality of compute nodes on a network, and identifying first and second virtual machines having inter-virtual machine communication over the network in an amount that is greater than a threshold amount of the network traffic. The method further comprises migrating at least one of the first and second virtual machines so that the first and second virtual machines are allocated to the same compute node and the inter-virtual machine communication between the first and second virtual machines is no longer directed over the network. In one embodiment, each compute node is coupled to an Ethernet link of a network switch, and data is obtained from a management information database of the network switch to determine the amount of network bandwidth that is being utilized for communication between the first and second virtual machines.

Abstract: A computer implemented method is provided, including monitoring the utilization of resources available within a compute node, wherein the resources include an input/output capacity, a processor capacity, and a memory capacity. The method further comprises allocating virtual machines to the compute node to maximize use of a first one of the resources; and then allocating an additional virtual machine to the compute node to increase the utilization of the resources other than the first one of the resources without over-allocating the first one of the resources. In a web server, the input/output capacity may be the resource to be maximized. However, unused memory capacity and/or processor capacity of the compute node may be used more effectively by identifying an additional virtual machine that is memory intensive or processor intensive to be allocated or migrated to the compute node.