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To ensure the QoS in Internet services, it is critical to detect the failures quickly and accurately. However, it is a difficult problem because one must extract and interpret fail patterns from large amounts of high-dimensional data. Presently, most technologies do not fit for large-scale system because of the complexity. Moreover, the detecting accuracy of them is relatively low. In this paper, we propose a general method which can deal with high-dimensional data efficiently and adapt for the updates of observed system. Furthermore, the detecting time grows slowly along with the sharp increase in the mount of data. An experiment is given afterwards to show how the method can be used and in the end a conclusion is drawn that the method can be effectively used to detect the failures in the application-level of Internet services.