Abstract: Techniques for cloning, writing to, and reading from file system metadata. Cloning involves identifying a first set of pointers included in a first root node in a file system metadata tree structure that stores file system metadata in leaf nodes of the tree structure, creating a first copy of the first root node that includes the first set of pointers, creating a second copy of the first root node that includes the first set of pointers, associating the first copy with a first view, and associating the second copy with a second view. Reading generally involves traversing the tree structure towards a target leaf node that contains data to be read. Writing generally involves traversing the tree structure in the same manner, but also creating copies of any nodes to be modified if those nodes are deemed to have a different treeID than a particular root node.

Abstract: Techniques for cloning, writing to, and reading from file system metadata. Cloning involves identifying a first set of pointers included in a first root node in a file system metadata tree structure that stores file system metadata in leaf nodes of the tree structure, creating a first copy of the first root node that includes the first set of pointers, creating a second copy of the first root node that includes the first set of pointers, associating the first copy with a first view, and associating the second copy with a second view. Reading generally involves traversing the tree structure towards a target leaf node that contains data to be read. Writing generally involves traversing the tree structure in the same manner, but also creating copies of any nodes to be modified if those nodes are deemed to have a different treelD than a particular root node.

Abstract: Techniques for cloning, writing to, and reading from file system metadata. Cloning involves identifying a first set of pointers included in a first root node in a file system metadata tree structure that stores file system metadata in leaf nodes of the tree structure, creating a first copy of the first root node that includes the first set of pointers, creating a second copy of the first root node that includes the first set of pointers, associating the first copy with a first view, and associating the second copy with a second view. Reading generally involves traversing the tree structure towards a target leaf node that contains data to be read. Writing generally involves traversing the tree structure in the same manner, but also creating copies of any nodes to be modified if those nodes are deemed to have a different treeID than a particular root node.

Abstract: A system and method for providing quality of service (QoS) for clients running on host computers to access a common resource uses a resource pool module and a local scheduler in at least one of the host computers. The resource pool module operates to compute an entitlement of each client for the common resource based on a current capacity for the common resource and demands of the clients for the common resource. In addition, the resource pool module operates to assign a portion of the computed current capacity for the common resource to a particular host computer using the computed entitlement of each client running on the particular host computer. The local scheduler operates to allocate the portion of the computed current capacity among the clients running on the particular host computer.

Abstract: A method of reducing power consumption of a server cluster of host systems with virtual machines executing on the host systems is provided. The method includes recommending host system power-on when there is a host system whose utilization is above a target utilization, and recommending host system power-off when there is a host system whose utilization is below the target utilization. Recommending host system power-on includes calculating impact of powering on a standby host system with respect to reducing the number of highly-utilized host systems in the server cluster. Recommending host system power-off includes calculating impact of powering off a host system with respect to decreasing the number of less-utilized host systems in the server cluster.

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: In an example, a method for performing initial placement of a data object in a distributed system that includes a plurality of hardware resources includes receiving a request to create an instance of a data object; determining, in response to the request, a list of hardware resources that satisfy one or more criteria of the data object; creating, in response to the request, a virtual cluster that includes a subset of the hardware resources included in the list of hardware resources; selecting a hardware resource from the virtual cluster into which the data object is to be placed; placing the data object into the hardware resource; and releasing the virtual cluster.

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: A system and method for performing resource allocation for a host computer cluster uses a copy of a cluster resource allocation hierarchy of the host computer cluster to generate a host resource allocation hierarchy of a host computer in the host computer cluster.

Abstract: A method of reducing power consumption of a server cluster of host systems with virtual machines executing on the host systems is disclosed. The method includes recommending host system power-on when there is a host system whose utilization is above a target utilization, and recommending host system power-off when there is a host system whose utilization is below the target utilization. Recommending host system power-on includes calculating impact of powering on a standby host system with respect to reducing the number of highly-utilized host systems in the server cluster. The impact of powering on is calculated by simulating moving some virtual machines from highly utilized host systems to the standby host system being recommended to be powered on. Recommending host system power-off includes calculating impact of powering off a host system with respect to decreasing the number of less-utilized host systems in the server cluster.

Abstract: One or more embodiments of the present invention provide a technique for effectively managing virtualized computing systems with an unlimited number of hardware resources. Host systems included in a virtualized computer system are organized into a scalable, peer-to-peer (P2P) network in which host systems arrange themselves into a network overlay to communicate with one another. The network overlay enables the host systems to perform a variety of operations, which include dividing computing resources of the host systems among a plurality of virtual machines (VMs), load balancing VMs across the host systems, and performing an initial placement of a VM in one of the host systems.

Abstract: One or more embodiments of the present invention provide a method for performing initial placement and load balancing of a data objects in a distributed system. The distributed system includes hardware resources, e.g., host systems and storage arrays, which are configured to execute and/or store data objects. A data object is initially placed into the distributed system by creating a virtual cluster of hardware resources that are compatible to execute and/or host the data object, and then selecting from the virtual cluster a hardware resource that is optimal for executing and/or hosting the data object. The data object is placed into the selected hardware resource, whereupon a load balancing operation is optionally performed across the virtual cluster. The virtual cluster is subsequently released, and the distributed system is returned to its original state with the data object included therein.

Abstract: A technique for predictive distributed resource scheduling and distributed power management includes analyzing patterns in the workload, predicting future workloads, and making recommendations for changes to the virtual computing environment. In addition, a cost-benefit analysis can be performed to determine whether the recommended change would likely result in improved performance.

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: Embodiments perform opportunistically proactive resource scheduling for a plurality of resource-consuming entities. The scheduling is based on both current entitlement (or demand) by the entities and predicted future entitlement (or demand) by the entities. Resources are allocated based on the current demands, while any remaining resource capacity is further allocated to entities based on predicted demands. In some embodiments, the scheduling is performed on a cluster of hosts executing a plurality of virtual machines (VMs) in a virtualized datacenter to implement load balancing.

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: One or more embodiments of the present invention provide a technique for effectively managing virtualized computing systems with an unlimited number of hardware resources. Host systems included in a virtualized computer system are organized into a scalable, peer-to-peer (P2P) network in which host systems arrange themselves into a network overlay to communicate with one another. The network overlay enables the host systems to perform a variety of operations, which include dividing computing resources of the host systems among a plurality of virtual machines (VMs), load balancing VMs across the host systems, and performing an initial placement of a VM in one of the host systems.

Abstract: A technique for predictive distributed resource scheduling and distributed power management includes analyzing patterns in the workload, predicting future workloads, and making recommendations for changes to the virtual computing environment. In addition, a cost-benefit analysis can be performed to determine whether the recommended change would likely result in improved performance.

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.