1. A method of anomaly detection in data centers, comprising: analyzing time series data for the data center by testing statistical hypotheses corresponding to different operational states of the data center; constructing upper and lower bounds based on the statistical hypotheses; and flagging anomalies in the time series data falling outside of the upper and lower bounds.