1. A method for electronic prognostication for a computer system, the method comprising: monitoring a performance parameter in a set of performance parameters from a set of computer systems that includes at least two computer systems, wherein monitoring the performance parameter includes systematically monitoring and recording the set of performance parameters from computer systems in the set of computer systems, and wherein the recording process keeps track of the temporal relationships between events in different performance parameters in the set of performance parameters; generating a training data set based on the performance parameter monitored from the set of computer systems, wherein generating the training data set includes concatenating two or more time-series of the performance parameter by appending each time-series from the two or more time-series to an end of a previous time-series from the two or more time-series, wherein each of the two or more time-series is obtained from a different computer system in the set of computer systems; training the pattern-recognition model using the training data set; using the pattern-recognition model to look for anomalies in performance parameters gathered during normal operation of a target computer system; and generating an alarm when the pattern-recognition model detects an anomaly in the performance parameters from the target computer system.