Abstract: A method and system for forecasting resource utilization of an information technology system having a plurality of system components. The method includes classifying the plurality of system components based on at least one resource utilization metric. The method also includes determining at least one reference component in each class from among the components classified within the respective class. The method also includes building a representative machine learning model for each reference component in each class. The method also includes applying the representative machine learning model to all system components within the respective class. Applying the representative machine learning model to all system components within the respective class forecasts the resource utilization of all system components in the information technology system without building a machine learning model for each system component in the information technology system.

Abstract: A production system and method for integrating machine learning models. The system includes a Model Development System having machine learning models, which perform predictions on input data received by the machine learning model. The system includes a Prediction System that receives an input message and generates prediction results based on predictions performed on input data from the received input message. The system includes at least one machine learning model adapter. The machine learning model adapter loads a corresponding machine learning model from the Model Development System, and provides input data to the loaded machine learning model, in which the input data is based on the input message received by the Prediction System. The machine learning model adapter also receives prediction value results from the loaded machine learning model based on predictions performed by the loaded machine learning model, and sends the prediction value results to the Prediction System.