A computer-implemented method for identifying and projecting recurrent event patterns in an Information Technology, IT, infrastructure, the method comprising: deriving at least one time period based on historical events data of the IT infrastructure, wherein the at least one time period is derived based on discontinuity periods in the historical events data, wherein a discontinuity period is a period of time during which no events occur; grouping the historical events data comprising a plurality of events captured for the IT infrastructure, based on the at least one time period to create a plurality of data points sets, wherein each data points set is associated with one of the at least one time period and comprises at least one event from the plurality of events; creating an event corpus comprising each of the plurality of events arranged based on frequency of occurrence across the plurality of data points sets; identifying at least one event that have highest frequency of occurrence within the event corpus; determining one or more data points sets from the plurality of data points sets in which the at least one event have occurred; and computing a projected frequency of occurrence of the at least one event in future time periods corresponding to the one or more data points sets, wherein said computing further comprises: increasing a respective frequency of occurrence by an amount equal to an average positive frequency variation across consecutive data points sets if a number of positive frequency variations is greater than a number of negative frequency variations; or decreasing the respective frequency of occurrence by an amount equal to an average negative frequency variation across consecutive data points sets if a number of negative frequency variations is greater than a number of positive frequency variations. deriving at least one time period based on historical events data of the IT infrastructure, wherein the at least one time period is derived based on discontinuity periods in the historical events data, wherein a discontinuity period is a period of time during which no events occur; grouping the historical events data comprising a plurality of events captured for the IT infrastructure, based on the at least one time period to create a plurality of data points sets, wherein each data points set is associated with one of the at least one time period and comprises at least one event from the plurality of events; creating an event corpus comprising each of the plurality of events arranged based on frequency of occurrence across the plurality of data points sets; identifying at least one event that have highest frequency of occurrence within the event corpus; determining one or more data points sets from the plurality of data points sets in which the at least one event have occurred; and computing a projected frequency of occurrence of the at least one event in future time periods corresponding to the one or more data points sets, wherein said computing further comprises: increasing a respective frequency of occurrence by an amount equal to an average positive frequency variation across consecutive data points sets if a number of positive frequency variations is greater than a number of negative frequency variations; or decreasing the respective frequency of occurrence by an amount equal to an average negative frequency variation across consecutive data points sets if a number of negative frequency variations is greater than a number of positive frequency variations. increasing a respective frequency of occurrence by an amount equal to an average positive frequency variation across consecutive data points sets if a number of positive frequency variations is greater than a number of negative frequency variations; or decreasing the respective frequency of occurrence by an amount equal to an average negative frequency variation across consecutive data points sets if a number of negative frequency variations is greater than a number of positive frequency variations.