Ai customized mlops framework in a multi-tenant cloud environment

Abstract

A computer implemented system, method, and computer program product are disclosed for managing a machine learning model operation (MLOps) for cost forecasting models. The MLOps receives a request for a subscription machine learning (ML) model by a tenant having a corresponding tenant configuration profile and automatically selects a subscription ML model in a model registry based on the tenant configuration profile. The MLOps deploys the selected subscription ML model to the tenant and monitors usage by the tenant of the currently operating ML model at a pre-determined refresh frequency. The MLOps determines whether the currently operating ML model exceeds a pre-determined accuracy threshold, and automatically deploys a second subscription ML model from the model registry to the tenant in place of the currently operating ML model in response to the pre-determined accuracy threshold being exceeded.