Abstract: A system and method for performing a resource allocation diagnosis on a distributed computer system includes computing current resource allocation of the distributed computer system using a current snapshot of the distributed computer system. The current snapshot includes configurations and resource usage information of at least some components of the distributed computer system. The system and method also includes computing improved resource allocation of the distributed computer system using a modified version of the current snapshot of the distributed computer system and outputting the current resource allocation and the improved resource allocation for the resource allocation diagnosis.

Abstract: A system and method for performing remote resource allocation analyzes on distributed computer systems utilizes a snapshot of a target distributed computer system obtained at a distributed computer system, which is transmitted to a remote resource allocation module so that a remote resource allocation analysis can be performed on the snapshot of the target distributed computer system. The snapshot includes configurations and resource usage information of at least some components of the target distributed computer system.

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 resource management system and method for performing resource management operations in a distributed computer system uses predicted resource demands for a specified time in the future to change a resource management option of a resource management analysis algorithm prior to the specified time so that the resource management analysis algorithm can be executed in anticipation of the predicted resource demands at the specified time.

Abstract: Systems and methods for finding solutions exhaustively in distributed load balancing are provided. A plurality of virtual machines (VMs) is in communication with a virtual machine management server (VMMS). The VMMS is configured to generate a matrix that represents a mapping of a plurality of virtual machines (VMs) to a plurality of hosts and to calculate a first imbalance metric of the matrix. The VMMS is also configured to identify a plurality of candidate migrations the VMs. The VMMS searches through the solution space efficiently and can perform an exhaustive search to find the optimal solution. For each candidate migration, the VMMS is configured to alter the matrix to represent the candidate migration and to calculate a candidate imbalance metric based on the altered matrix. The VMMS is also configured to determine which candidate migration to perform based at least in part on the candidate imbalance metric for each candidate migration and the first imbalance metric.

Abstract: Embodiments of a non-transitory computer-readable storage medium and a computer system are disclosed. In an embodiment, a non-transitory computer-readable storage medium containing program instructions for managing host computers that run virtual machines into host-groups within a cluster is disclosed. When executed, the instructions cause one or more processors to perform steps including determining if a virtual machine entity needs additional resources and, if the virtual machine entity needs additional resources, mapping a host computer to a host-group with which the virtual machine entity is associated.

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 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 method for adjusting the configuration of host computers in a cluster on which virtual machines are running in response to a failed change in state is disclosed. The method involves receiving at least one reason a change in state failed the present check or the future check, associating the at least one reason with at least one remediation action, wherein the remediation action would allow the change in state to pass both a present check and a future check, assigning the at least one remediation action a cost, and determining a set of remediation actions to perform based on the cost assigned to each remediation action. 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 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 power management system and method for performing power management operations in a distributed computer system uses predicted resource demands for a specified time in the future to change a power management option of a power management analysis algorithm prior to the specified time so that the power management analysis algorithm can be executed in anticipation of the predicted resource demands at the specified time.

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: 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 module and method for automatically scaling a multi-tier application, wherein each tier of the multi-tier application is supported by at least one virtual machine, selects one of reinforced learning and heuristic operation based on a policy to recommend a scaling action from a current state of the multi-tier application. If reinforced learning is selected, the reinforced learning is applied to select the scaling action from a plurality of possible actions for the multi-tier application in the current state. If heuristic operation is selected, the heuristic operation is applied to select the scaling action using a plurality of defined heuristics.

Abstract: A system and method for performing a hypothetical power management analysis on a distributed computer system uses chronologically consecutive snapshots of the distributed computer system. The snapshots are used to extract demands of clients running in the distributed computer system for a resource for different time intervals, which are then stitched together to produce a workload trace. The snapshots and the workload trace are used to construct modeling scenarios for the distributed computer system. The modeling scenarios are used to perform analyses to simulate the operation of the distributed computer system during which the power management module is enabled to compute potential power savings.

Abstract: A system and method for performing customized remote resource allocation analyses on distributed computer systems utilizes a snapshot of a distributed computer system, which is received at a remote resource allocation module, to perform a resource allocation analysis using a resource allocation algorithm. The resource allocation algorithm is selected from a plurality of resource allocation algorithms based on at least one user-provided parameter associated with the distributed computer system.

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.

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: pa Systems and methods for finding solutions exhaustively in distributed load balancing are provided. A plurality of virtual machines (VMs) is in communication with a virtual machine management server (VMMS). The VMMS is configured to generate a matrix that represents a mapping of a plurality of virtual machines (VMs) to a plurality of hosts and to calculate a first imbalance metric of the matrix. The VMMS is also configured to identify a plurality of candidate migrations the VMs. The VMMS searches through the solution space efficiently and can perform an exhaustive search to find the optimal solution. For each candidate migration, the VMMS is configured to alter the matrix to represent the candidate migration and to calculate a candidate imbalance metric based on the altered matrix. The VMMS is also configured to determine which candidate migration to perform based at least in part on the candidate imbalance metric for each candidate migration and the first imbalance metric.

Abstract: A system and method for performing resource allocation analyses on hypothetical distributed computer systems uses a user-modified snapshot of a hypothetical distributed computer system to execute a resource allocation analysis. The user-modified snapshot includes configurations and resource usage information of at least some components of the hypothetical distributed computer system.