Resource provisioning planning for enterprise migration and automated application discovery

摘要

A method and a system may automatically compute optimized target resources and identify configurations given discovered source properties and dependencies of machines, while prioritizing performance in the target environment. An algorithm and/or tools for programmatically identifying and locating business application instances in an infrastructure, based on weighted similarity metric may be also provided.

主权项

1. A method of resource provisioning planning, comprising:
receiving source site data comprising parameters associated with a source site, the source site comprising information technology infrastructure of an enterprise, the information technology infrastructure comprising at least a plurality of servers and a plurality of applications; discovering network dependencies between the plurality of servers of the source site; discovering application instances and dependencies on the plurality of servers, based on a weighted similarity metric; identifying one or more server misconfigurations; determining potential server consolidation; determining a target platform for migrating the plurality of servers; mapping each of the plurality of servers to a virtual machine of a plurality of virtual machines subject to resource constraints of the servers and the virtual machines; clustering the virtual machines based on network dependencies of the servers mapped to the virtual machines; determining whether an existing target server can fit a candidate cluster; responsive to determining that the existing target server can fit the candidate cluster, placing the candidate cluster on the existing target server; responsive to determining that the existing target server cannot fit the candidate cluster, selecting a new target server to fit the candidate cluster with minimum cost; and repeating the determining of whether an existing target server can fit a candidate cluster, one or more of the placing and the selecting, for a next candidate cluster.