Abstract:
A universal resource management system and method for performing resource management operations for different computing environments uses a universal snapshot of the different computing environments to perform a resource management analysis to produce at least one recommended action for the different computing environments. The universal snapshot is created using state information collected from the different computing environments. The recommended action is then implemented in at least one of the different computing environments.
Abstract:
A method for supporting a change in state within a cluster of host computers that run virtual machines is disclosed. The method involves identifying a change in state within a cluster of host computers that run virtual machines, determining if predefined criteria for available resources within the cluster of host computers can be met by resources available in the cluster of host computers, and determining if predefined criteria for available resources within the cluster of host computers can be maintained after at least one different predefined change in state. In an embodiment, the steps of this method may be implemented in a non-transitory computer-readable storage medium having instructions that, when executed in a computing device, causes the computing device to carry out the steps.
Abstract:
A power monitoring system and method for computing power cost savings of power management operations in a cluster of host computers uses power usage information from the host computers in the cluster with power sensing capabilities and power management information from a power management module, which includes times when at least one of the host computers was powered down, to compute the power cost savings attributable to the power management operations executed by the power management module.
Abstract:
A system and method for autoscaling a multi-tier application, that has components executing on a plurality of tiers of a virtual data center, allocates resources to each of the plurality of tiers based on cost and performance. An application performance is determined, and a new application performance is estimated based at least partially on an application reservation and an application limit. An optimized utility of the application is calculated based on the cost to execute the application, the application reservation, and the application limit. A scaling factor for each tier is then determined to scale up or down a number of virtual machines operating in each of the tiers.
Abstract:
Disclosed are aspects of resource allocation diagnosis for distributed computer systems. In one example, a user interface creates a user-modified version of a snapshot of a distributed computing system. A hypothetical resource allocation is determined for the user-modified version of the snapshot. The hypothetical resource allocation is calculated based on at least one of load balancing and resource scheduling. The hypothetical resource allocation for the user-modified version of the snapshot is implemented in the distributed computing system.
Abstract:
A management server and method for performing resource management operations in a distributed computer system takes into account information regarding multi-processor memory architectures of host computers of the distributed computer system, including information regarding Non-Uniform Memory Access (NUMA) architectures of at least some of the host computers, to make a placement recommendation to place a client in one of the host computers.
Abstract:
Disclosed are aspects of resource allocation diagnosis for distributed computer systems. In one example, a current snapshot of a distributed computing system is created. A current resource allocation of the distributed computing system is computed using the current snapshot of the distributed computing system. A modified snapshot is generated using the current snapshot. The modified snapshot includes a user modification. A hypothetical resource allocation is computed using the modified snapshot. A user interface includes the current resource allocation and the hypothetical resource allocation.
Abstract:
A resource management system and method for performing resource management operations in a distributed computer system uses a dispersion rule to try to uniformly disperse clients in a cluster of host computers in the distributed computer system. The dispersion rule is used to compute a dispersion score for at least one candidate distribution of the clients in the cluster of host computers, which is used to select a particular candidate distribution of the clients in the cluster of host computers to disperse the clients.
Abstract:
A system and method for autoscaling a multi-tier application, that has components executing on a plurality of tiers of a virtual data center, allocates resources to each of the plurality of tiers based on cost and performance. An application performance is determined, and a new application performance is estimated based at least partially on an application reservation and an application limit. An optimized utility of the application is calculated based on the cost to execute the application, the application reservation, and the application limit. A scaling factor for each tier is then determined to scale up or down a number of virtual machines operating in each of the tiers.
Abstract:
A system and method for managing resources in a distributed computer system that includes at least one resource pool for a set of virtual machines (VMs) utilizes a set of desired individual VM-level resource settings that corresponds to target resource allocations for observed performance of an application running in the distributed computer system. The set of desired individual VM-level resource settings are determined by constructing a model for the observed application performance as a function of current VM-level resource allocations and then inverting the function to compute the target resource allocations in order to meet at least one user-defined service level objective (SLO). The set of desired individual VM-level resource settings are used to determine final RP-level resource settings for a resource pool to which the application belongs and final VM-level resource settings for the VMs running under the resource pool, which are then selectively applied.