Abstract: Placement scenario optimization mechanisms for automatic placement of computing entities onto nodes of a running multi-node computing cluster. A set of failure mode parameters define a high-availability requirement of the multi-node computing cluster. In advance of a failure event, and responsive to a determination that a then-current computing entity placement does not satisfy the high-availability requirement, the cluster is analyzed and a plurality of feasible placement scenarios are generated. Optimization criteria are applied to the feasible placement scenarios such that a best choice from among the feasible placement scenarios is identified and applied to the virtual machine placements over the cluster. A change monitoring and detection facility continually observes the multi-node computing cluster to detect a change of a failure mode parameter or to detect a change to the configuration of the virtual machines.

Abstract: Placement scenario optimization mechanisms for automatic placement of computing entities onto nodes of a running multi-node computing cluster. A set of failure mode parameters define a high-availability requirement of the multi-node computing cluster. In advance of a failure event, and responsive to a determination that a then-current computing entity placement does not satisfy the high-availability requirement, the cluster is analyzed and a plurality of feasible placement scenarios are generated. Optimization criteria are applied to the feasible placement scenarios such that a best choice from among the feasible placement scenarios is identified and applied to the virtual machine placements over the cluster. A change monitoring and detection facility continually observes the multi-node computing cluster to detect a change of a failure mode parameter or to detect a change to the configuration of the virtual machines.

Abstract: Placement scenario optimization mechanisms for automatic placement of computing entities onto nodes of a running multi-node computing cluster. A set of failure mode parameters define a high-availability requirement of the multi-node computing cluster. In advance of a failure event, and responsive to a determination that a then-current computing entity placement does not satisfy the high-availability requirement, the cluster is analyzed and a plurality of feasible placement scenarios are generated. Optimization criteria are applied to the feasible placement scenarios such that a best choice from among the feasible placement scenarios is identified and applied to the virtual machine placements over the cluster. A change monitoring and detection facility continually observes the multi-node computing cluster to detect a change of a failure mode parameter or to detect a change to the configuration of the virtual machines.

Abstract: Placement scenario optimization mechanisms for automatic placement of computing entities onto nodes of a running multi-node computing cluster. A set of failure mode parameters define a high-availability requirement of the multi-node computing cluster. In advance of a failure event, and responsive to a determination that a then-current computing entity placement does not satisfy the high-availability requirement, the cluster is analyzed and a plurality of feasible placement scenarios are generated. Optimization criteria are applied to the feasible placement scenarios such that a best choice from among the feasible placement scenarios is identified and applied to the virtual machine placements over the cluster. A change monitoring and detection facility continually observes the multi-node computing cluster to detect a change of a failure mode parameter or to detect a change to the configuration of the virtual machines.

Abstract: Placement scenario optimization mechanisms for automatic placement of computing entities onto nodes of a running multi-node computing cluster. A set of failure mode parameters define a high-availability requirement of the multi-node computing cluster. In advance of a failure event, and responsive to a determination that a then-current computing entity placement does not satisfy the high-availability requirement, the cluster is analyzed and a plurality of feasible placement scenarios are generated. Optimization criteria are applied to the feasible placement scenarios such that a best choice from among the feasible placement scenarios is identified and applied to the virtual machine placements over the cluster. A change monitoring and detection facility continually observes the multi-node computing cluster to detect a change of a failure mode parameter or to detect a change to the configuration of the virtual machines.

Abstract: Various embodiments set forth one or more non-transitory computer-readable media storing program instructions that, when executed by one or more processors, cause the one or more processors to perform steps of determining at least one physical resource of a node in a cluster of nodes is under contention by virtual computing instances or a virtual computing instance cannot be placed on the cluster of nodes, determining a placement for one or more virtual computing instances on the cluster of nodes, each virtual computing instance having a virtual resource associated with a profile that is compatible with a profile associated with a physical resource of a node on which the virtual computing instance is placed, and generating and executing a plan to achieve the placement, the plan including at least one of migrating at least one virtual computing instance or reconfiguring a profile associated with at least one physical resource.