Cloud and Hybrid-Cloud Production Management System

A system includes a processor, and a memory storing software code and a machine learning (ML) model trained to allocate media production resources. The processor executes the software code to receive data describing a media flow requiring processing, identify, using the data and the ML model, media production resources for processing the described media flow, obtain the media production resources, and aggregate, from each of the media production resources, performance and billing metrics of a respective one of the media production resources resulting from processing of the described media flow by the media production resources. The processor may further execute the software code to determine, using the aggregated performance and billing metrics, a resource allocation efficiency score corresponding to each of one or more of the media production resources to provide one or more resource allocation efficiency score(s), and further train, using the resource allocation efficiency score(s), the ML model.

BACKGROUND

Media production facilities typically rely on local software defined networks (SDNs) to efficiently move media flows and coordinate media production. In traditional media production environments, these SDNs for managing media flows are implemented using “on-premises” resources for which the production facility has control of the information technology (IT) architecture. In addition, the actual work of media production is often performed using on-premises hardware resources and on-premises human expertise.

However, as highly scalable cloud-based virtual resources become increasingly available and affordable, and as automation solutions become increasingly proficient in replicating the performance of human contributors to media production, the transition to cloud-based and hybrid cloud/on-premises (hereinafter “cloud and hybrid-cloud”) media production grows more attractive. However, in the present cloud-based resource environment, production resources are typically provided a la carte by a variety of different vendors, so that a media production facility must normally obtain computing and storage resources under a contract with a particular vendor, arrange for media flow transfer bandwidth from another vendor, license media production software applications from yet other vendors, and so forth. Consequently, there is a need in the art for systems providing consolidated cloud and hybrid-cloud production management.