Abstract: Various examples are disclosed for cluster resource management using adaptive memory demands. In some examples, a local memory estimate is determined for a workload. The local memory estimate is determined using a memory reclamation parameter for the workload executed by a current host of the workload. A destination memory estimate is also determined for the workload. The destination memory estimate is determined using a full memory estimate unreduced by memory reclamation parameters. The workload is executed using a host that is selected in view of an analysis that uses the local memory estimate for the current host and the destination memory estimate for at least one destination host.

Abstract: Various examples are disclosed for cluster resource management using adaptive memory demands. In some examples, a local memory estimate is determined for a workload. The local memory estimate is determined using a memory reclamation parameter for the workload executed by a current host of the workload. A destination memory estimate is also determined for the workload. The destination memory estimate is determined using a full memory estimate unreduced by memory reclamation parameters. The workload is executed using a host that is selected in view of an analysis that uses the local memory estimate for the current host and the destination memory estimate for at least one destination host.

Abstract: Various examples are disclosed for cluster resource management using adaptive memory demands. Some aspects involve determining a destination memory estimate and a local memory estimate for various workloads executing in a datacenter. Goodness scores are determined corresponding to the candidate workload being executed on a number of different hosts. The goodness scores are determined using the local memory estimates for the currently executing workloads, the destination memory estimate is utilized for the candidate workload if it is not executing on the corresponding host. The workloads are balanced based on the goodness scores.

Abstract: Various examples are disclosed for cluster resource management using adaptive memory demands. Some aspects involve determining a destination memory estimate and a local memory estimate for various workloads executing in a datacenter. Goodness scores are determined corresponding to the candidate workload being executed on a number of different hosts. The goodness scores are determined using the local memory estimates for the currently executing workloads, the destination memory estimate is utilized for the candidate workload if it is not executing on the corresponding host. The workloads are balanced based on the goodness scores.