A computer-implemented method provides an early warning of an impending failure in a monitored system. The method includes performing, by a processor, an offline model learning process that generates a model of expected log rates in the monitored system from historical log data. The model represents a normal behavior of the monitored system. The method further includes performing an online detection process that detects the impending failure in the monitored system prior to an actual occurrence thereof based on (i) the model of expected log rates and (ii) observed log rates. The method also includes displaying, by a display device based on (i) the model of expected log rates and (ii) observed log rates in the monitored system, information relating to the impending failure prior to the actual occurrence of the impending failure. The online detection process identifies short term and long term failures and long term failures.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A computer-implemented method for providing an early warning of an impending failure in a monitored system, the method comprising: performing, by a processor, an offline model learning process that generates a model of expected log rates in the monitored system from historical log data, the expected log rates of the model representing a normal behavior of the monitored system; performing, by the processor, an online detection process that detects the impending failure in the monitored system prior to an actual occurrence of the impending failure based on (i) the model of expected log rates and (ii) observed log rates in the monitored system; and displaying, by a display device based on (i) the model of expected log rates and (ii) observed log rates in the monitored system, information relating to the impending failure prior to the actual occurrence of the impending failure, wherein the online detection process identifies short term failures and long term failures in the monitored system. 2. The computer-implemented method of claim 1, wherein the offline learning process comprises generating a plurality of time series from the historical log data, and wherein the model of the expected log rates of the monitored system is generated based on the plurality of time series. 3. The computer-implemented method of claim 2, wherein the model of the expected log rates of the monitored system includes the expected log rates in the monitored system for different times of a day. 4. The computer-implemented method of claim 2, further comprising updating the model based on newly observed log rates in the monitored system. 5. The computer-implemented method of claim 1, wherein the online detection process evaluates the model of expected log rates in the monitored system against the observed log rates in the monitored system to identify the impending failures. 6. The computer-implemented method of claim 1, wherein said online detection process maintains a running history of deviations between the expected log rates from the model and the observed log rates in the monitored system, and raises a failure signal when continuous deviations are detected greater than a threshold time period. 7. The computer-implemented method of claim 1, further comprising controlling a false alarm rate of the monitored system using at least one statistical based method applied to the historical log data. 8. The computer-implemented method of claim 1, further comprising controlling an operation of the monitored system based on a detection of the impending failure in order to prevent the impending failure or mitigate undesirable results of the impending failure. 9. The computer-implemented method of claim 8, wherein controlling the operation of the monitored system comprises powering down one or more machines that will at least one of (i) likely cause the impending failure of one or more other machines, (ii) suffer the impending failure, and (ii) will be undesirably affected by the impending failure. 10. The computer-implemented method of claim 1, wherein the information relating to the impending failure is displayed as one or more graphs. 11. The computer-implemented method of claim 1, wherein the information relating to the impending failure includes a time point at which failure symptoms began. 12. The computer-implemented method of claim 1, wherein the historical log data comprises historical log rate observations, and the method further comprises removing one or more of the historical log rate observations from the historical log data as being noisy based on statistical significance to other ones of the historical log rate observations, the one or more removed historical log rate observations being unconsidered by the offline model learning process in generating the model of expected log rates. 13. The computer-implemented method of claim 12, further comprising determining the statistical significance of the one or more of the historical log rate observations to the other ones of the historical log rate observations using one or more non-parameterized statistical methods. 14. The computer-implemented method of claim 1, distinguishing between short term failures and long term failures based on different time-based metrics, and wherein the information displayed in said displaying step includes an identification of which type of failure is implemented from among the short term failure and the long term failure. 15. The computer-implemented method of claim 1, wherein said displaying step comprises identifying the impending failure as a long term failure, responsive to a number of deviations, between the expected log rates from the model and the observed log rates in the monitored system, increasing over time. 16. A computer program product for providing an early warning of an impending failure in a monitored system, the computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to perform a method comprising: performing, by a processor, an offline model learning process that generates a model of expected log rates in the monitored system from historical log data, the expected log rates of the model representing a normal behavior of the monitored system; performing, by the processor, an online detection process that detects the impending failure in the monitored system prior to an actual occurrence of the impending failure based on (i) the model of expected log rates and (ii) observed log rates in the monitored system; and displaying, by a display device based on (i) the model of expected log rates and (ii) observed log rates in the monitored system, information relating to the impending failure prior to the actual occurrence of the impending failure, wherein the online detection process identifies short term failures and long term failures in the monitored system. 17. The computer program product of claim 16, wherein said online detection process maintains a running history of deviations between the expected log rates from the model and the observed log rates in the monitored system, and raises a failure signal when continuous deviations are detected greater than a threshold time period. 18. The computer program product of claim 16, wherein the method further comprises controlling an operation of the monitored system based on a detection of the impending failure in order to prevent the impending failure or mitigate undesirable results of the impending failure. 19. The computer program product of claim 18, wherein controlling the operation of the monitored system comprises powering down one or more machines that will at least one of (i) likely cause the impending failure of one or more other machines, (ii) suffer the impending failure, and (ii) will be undesirably affected by the impending failure. 20. A computer processing system for providing an early warning of an impending failure in a monitored system, the computer processing system comprising: a processor, configured to: perform an offline model learning process that generates a model of expected log rates in the monitored system from historical log data, the expected log rates of the model representing a normal behavior of the monitored system; and perform an online detection process that detects the impending failure in the monitored system prior to an actual occurrence of the impending failure based on (i) the model of expected log rates and (ii) observed log rates in the monitored system; and a display device, configured to display, based on (i) the model of expected log rates and (ii) observed log rates in the monitored system, information relating to the impending failure prior to the actual occurrence of the impending failure, wherein the online detection process identifies short term failures and long term failures in the monitored system.