A method for analysing a resource consumption in a computing infrastructure, said computing infrastructure comprising a plurality of computing devices for predicting a resource consumption anomaly on a computing device, said method comprising: - a step of determining, for a given period comprising a plurality of time intervals, a plurality of resource consumption modelling functions, each of said functions modelling the time change of the consumption of a resource for a time interval of the period, the determination step being performed for at least a first resource and a resource to be predicted; - a step of determining correlation between said resource consumption modelling functions, said correlation determination step including calculating at least one correlation between modelling functions for different time intervals; - a step of measuring a resource consumption, said step including measuring a consumption value of the first resource; and - a step of predicting the resource consumption of the computing infrastructure, said prediction step including calculating a future consumption value of the resource to be predicted from the consumption value of the first resource and a correlation previously calculated between modelling functions, said correlation previously calculated then corresponding to a correlation between a modelling function of the first resource and a modelling function of the resource to be predicted; said method being characterised in that it comprises: - a step of searching for a proximity between modelling functions and creating a plurality of groups of modelling functions including modelling functions classified as identical or similar upon proximity searching, said proximity searching being performed between modelling functions of a same resource and of different given periods; - a step of identifying a repetition rate of the modelling functions and selecting, for each time interval, a modelling function most representative of this time interval for a set of considered periods, the repetition rate corresponding to the occurrence rate of an identical or similar modelling function over different periods and over substantially identical time intervals. - a step of determining, for a given period comprising a plurality of time intervals, a plurality of resource consumption modelling functions, each of said functions modelling the time change of the consumption of a resource for a time interval of the period, the determination step being performed for at least a first resource and a resource to be predicted; - a step of determining correlation between said resource consumption modelling functions, said correlation determination step including calculating at least one correlation between modelling functions for different time intervals; - a step of measuring a resource consumption, said step including measuring a consumption value of the first resource; and - a step of predicting the resource consumption of the computing infrastructure, said prediction step including calculating a future consumption value of the resource to be predicted from the consumption value of the first resource and a correlation previously calculated between modelling functions, said correlation previously calculated then corresponding to a correlation between a modelling function of the first resource and a modelling function of the resource to be predicted; - a step of searching for a proximity between modelling functions and creating a plurality of groups of modelling functions including modelling functions classified as identical or similar upon proximity searching, said proximity searching being performed between modelling functions of a same resource and of different given periods; - a step of identifying a repetition rate of the modelling functions and selecting, for each time interval, a modelling function most representative of this time interval for a set of considered periods, the repetition rate corresponding to the occurrence rate of an identical or similar modelling function over different periods and over substantially identical time intervals.