The invention discloses an intelligent detection method for server exception of a hybrid strategy. The method comprises a historical data acquisition and analysis step and a real-time anomaly alarm step, wherein the historical data acquisition and analysis step comprises the steps of acquiring server historical data in a preset time period, preprocessing the historical data, screening out featuresneeding to be analyzed, and taking data corresponding to each feature as a time sequence, determining a normal value and an abnormal value corresponding to each time sequence in the historical data in combination with a time sequence decomposition algorithm and a Grubbs test algorithm; calculating a normal threshold value corresponding to each feature in the historical data, i.e., a maximum valuerange and a minimum value range of a normal value in each time sequence; and taking all time sequences in the historical data as training samples, establishing a plurality of abnormal data detectionmodels to predict and judge the to-be-detected sample, and outputting the probability that the to-be-detected sample is abnormal, so as to analyze the real-time data in the real-time alarm step.