Learning model to optimize automatic workload migration

Abstract

Metrics, including cost and latency, corresponding to a public computing system are monitored. A determination to migrate a workload running at donor computing system may be made based on the monitored metrics. A learning model, which may be initialized based on factors from a migration rules engine function, may make recommendations to migrate a workload based on a training data corpus. The learning model may be trained based on manual selections, or acceptances, of recommendations Automatic migration of a workload, under control of the learning model, may be made if recommendations are selected or accepted more frequently than an automatic migration criterion. Different learning models may be used to determine to migrate different corresponding workloads.