Abstract:
Disclosed herein are embodiments for managing the placement of virtual machines in a virtual machine network. In an embodiment, a method involves determining whether to separate at least one virtual machine in a set of virtual machines supporting a process and running on a first host computer from other virtual machines in the set. If at least one virtual machine is to be separated, then at least one virtual machine is selected based on a number of memory pages changed. The selected virtual machine is then separated from the other virtual machines in the set.
Abstract:
A method, a non-transitory computer-readable storage medium, and a computer system for managing the placement of virtual machines in a virtual machine network are disclosed. In an embodiment, a method involves determining if at least one virtual machine in a set of virtual machines supporting a process and running on a first host computer needs to be separated from other virtual machines in the set. If at least one virtual machine needs to be separated, then at least one virtual machine is selected to be separated based on the number of memory pages changed. The selected VM is then separated from the other virtual machines in the set.
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 technique for managing distributed computing resources in a virtual computing environment is disclosed. In an embodiment, a method includes receiving a recommended change to a virtual architecture of a virtual computing environment; determining an impact on current workload in the virtual computing environment if the recommended change is performed; determining an impact on future workload in the virtual computing environment if the recommended change is performed; calculating a combined impact on current and future workload; determining if the combined impact is above or below a threshold; if the combined impact on current and future workload is below the threshold, do not perform the recommended change; and if the combined impact on current and future workload is above the threshold, perform the recommended change.
Abstract:
A management server and method for performing resource management operations in a distributed computer system uses at least one sampling parameter to estimate demand of a client for a resource. The sampling parameter has a correlation with at least one target performance goal of an application that the client is running. The demand estimation can then be used to make at least one decision in a resource management operation.
Abstract:
Methods and systems to reconfigure clusters in elastic multi-tenant cloud computing system. An example method includes partitioning a first resource reservation of a first virtual data center between a first cluster and a second cluster and partitioning a second resource reservation of a second virtual data center between the first cluster and the second cluster, and based on the partitioning of the first resource reservation and the second resource reservation, collectively adjusting a first portion of the first resource reservation allotted to the first cluster and a second portion of the second resource reservation allotted to the first cluster in a same reconfiguration operation.
Abstract:
A technique for managing distributed computing resources in a virtual computing environment is disclosed. In an embodiment, a method includes receiving a recommended change to a virtual architecture of a virtual computing environment; determining an impact on current workload in the virtual computing environment if the recommended change is performed; determining an impact on future workload in the virtual computing environment if the recommended change is performed; calculating a combined impact on current and future workload; determining if the combined impact is above or below a threshold; if the combined impact on current and future workload is below the threshold, do not perform the recommended change; and if the combined impact on current and future workload is above the threshold, perform the recommended change.
Abstract:
In one embodiment, a method for placing virtual machines in a collection is provided. A plurality of equivalence sets of hosts is determined prior to placing virtual machines in the collection. The hosts in an equivalence set of hosts are considered similar. An equivalence set of hosts in the plurality of equivalence sets is selected to place the virtual machines in the collection. The method then places at least a portion of the virtual machines in the collection on one or more hosts in the selected equivalence set of hosts.
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 management server and method for performing resource management operations in a distributed computer system uses at least one sampling parameter to estimate demand of a client for a resource. The sampling parameter has a correlation with at least one target performance goal of an application that the client is running. The demand estimation can then be used to make at least one decision in a resource management operation.