1. A virtualization layer that is executed on one or more processors of a computer system that additionally includes memory data-storage devices, and networking components and that creates a execution environment for a number of virtual machines, the virtualization layer including: a machine-learned model that predicts operational characteristics of the computer system from input resource-allocation-state vectors that each describes the resource-allocation state of a different virtual machine; and a resource-allocation component that allocates computational resources to virtual machines, the resource-allocation component processing a request that entails changing the resource-allocation state of a virtual machine by, generating a set of resource-allocation-state vectors that describe the resource-allocation states of the number of virtual machines in memory, inputting the generated set of resource-allocation-state vectors to the machine-learned model, receiving, from the machine-learned model, predicted operational characteristics of the computer system for the number of virtual machines with resource allocation states described by the generated set of resource-allocation-state vectors, and when the predicted operational characteristics indicate operational non-optimality, unpredictability, and/or instability, modifying processing of the request to prevent the predicted operational non-optimality, unpredictability, add/or instability, wherein the operational characteristics predicted by the machine-learned model include utilizations for each of one or more computational resources by each of the number of virtual machines.