Systems, methods and tools for managing the job queues of virtual machines, maintaining a low energy profile and a quality of service within the contractual service agreement. The systems migrate jobs to a new VM queue when a assigned VM has failed. The systems employ machine learning techniques to make decisions whether or not to reallocate the job to a VM running in an active mode (non-scalable mode) or a VM operating under a dynamic voltage and frequency scaling (DVFS) mode. The systems reconcile job failures, transfer and/or complete jobs using the network of VMs without degrading the service quality, maintaining a lower power consumption policy through scalable modes, including idle, busy, sleep, DVFS gradient and DVFS maximum modes, improving the overall reliability of the data center by switching the jobs to scalable nodes, increasing the recoverability of the systems in the virtualized environments.