Machine learning prediction of virtual computing instance transfer performance

Abstract

The disclosure provides an approach for preventing the failure of virtual computing instance transfers across data centers. In one embodiment, a flow control module collects performance information primarily from components in a local site, as opposed to components in a remote site, during the transfer of a virtual machine (VM) from the local site to the remote site. The performance information that is collected may include various performance metrics, each of which is considered a feature. The flow control module performs feature preparation by normalizing feature data and imputing missing feature data, if any. The flow control module then inputs the prepared feature data into machine learning model(s) which have been trained to predict whether a VM transfer will succeed or fail, given the input feature data. If the prediction is that the VM transfer will fail, then remediation actions may be taken, such as slowing down the VM transfer.