A traffic manager (69, 134) for a distributed data storage system, comprising: an iterative spike identifier configured to identify, using N spike thresholds, N respective levels of traffic spikes in traffic data on an account basis in a distributed data storage system, where N is greater than zero, wherein the iterative spike identifier is configured to summarize the traffic data into quartiles and to calculate a first spike threshold based on a sum of a third quartile Q3 and an interquartile range IQR for the first level of traffic spikes multiplied by a factor k, and wherein the iterative spike identifier is further configured to iteratively identify N-1 additional levels of traffic spikes by: defining an array variable WS and copying a traffic series S to the array variable, wherein the traffic series is a data set comprising samples exceeding the first spike threshold; setting a traffic level to zero; and repeating: counting a number N of samples in WS; determining whether N is less than a predetermined threshold TH1; if N is more than TH1, generating a mean, a median, a standard deviation, a first quartile Q1, a third quartile Q3 and an interquartile range IQR for WS; calculating a spike threshold (230, 260) equal to Q3 + s*IQR, where s is a constant; separating WS into regular fluctuation RS below the spike threshold and spike fluctuations SS above the spike threshold; deleting traffic fluctuations from the array variable WS; increasing the traffic level by one; and replacing WS with SS; until a condition is met that ends the loop, wherein the condition is occurrence of an event, completion of a predetermined number of cycles, or the determination that N is less than or equal to TH1; and a traffic cycle identifier configured to identify whether cyclic traffic spikes are present in each of the traffic levels for each of a plurality of accounts using autocorrelation on the traffic data and peak detection in autocorrelation data; and a partition manager configured to communicate with the traffic cycle identifier and to selectively partition one of the plurality of accounts based on based on the autocorrelation and the peak detection, wherein the traffic manager is further configured to predict when a next spike will occur based on the identified traffic spikes and to apply additional resources in advance of an anticipated spike to balance a traffic load. defining an array variable WS and copying a traffic series S to the array variable, wherein the traffic series is a data set comprising samples exceeding the first spike threshold; setting a traffic level to zero; and repeating: counting a number N of samples in WS; determining whether N is less than a predetermined threshold TH1; if N is more than TH1, generating a mean, a median, a standard deviation, a first quartile Q1, a third quartile Q3 and an interquartile range IQR for WS; calculating a spike threshold (230, 260) equal to Q3 + s*IQR, where s is a constant; separating WS into regular fluctuation RS below the spike threshold and spike fluctuations SS above the spike threshold; deleting traffic fluctuations from the array variable WS; increasing the traffic level by one; and replacing WS with SS; counting a number N of samples in WS; determining whether N is less than a predetermined threshold TH1; if N is more than TH1, generating a mean, a median, a standard deviation, a first quartile Q1, a third quartile Q3 and an interquartile range IQR for WS; calculating a spike threshold (230, 260) equal to Q3 + s*IQR, where s is a constant; separating WS into regular fluctuation RS below the spike threshold and spike fluctuations SS above the spike threshold; deleting traffic fluctuations from the array variable WS; increasing the traffic level by one; and replacing WS with SS; until a condition is met that ends the loop, wherein the condition is occurrence of an event, completion of a predetermined number of cycles, or the determination that N is less than or equal to TH1; and a traffic cycle identifier configured to identify whether cyclic traffic spikes are present in each of the traffic levels for each of a plurality of accounts using autocorrelation on the traffic data and peak detection in autocorrelation data; and a partition manager configured to communicate with the traffic cycle identifier and to selectively partition one of the plurality of accounts based on based on the autocorrelation and the peak detection, wherein the traffic manager is further configured to predict when a next spike will occur based on the identified traffic spikes and to apply additional resources in advance of an anticipated spike to balance a traffic load.