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Ensuring the availability of cloud computing services always concerns both service providers and end users. Therefore, the system always needs precautions for unexpected cases. Accordingly, cloud computing services mustbe capable of identifying faults and behaving appropriatelywhen it is abnormal to ensure the smoothness as well asthe service quality. In this study, we propose a fault detection method for multi-tier web application in cloud computing deployment environment based on the Fuzzy Oneclass support vector machine and Exponentially WeightedMoving Average method. And then, the suspicious metrics are located by using feature selection method whichbased on Random Forest algorithm. To evaluate our approach, a multi-tier application is deployed by a transnational web e-Commerce benchmark by using TPC-W (TPCBenchmark™ W, simulates the activities of a business oriented transaction web server in a controlled internet commerce environment) in private cloud and then it is injectedtypical faults. The effectiveness of the fault detection anddiagnosis are demonstrated in experiment results.