Abstract: A method for metrics-based anomaly detection involves receiving an anomaly analysis request for an asset and obtaining metrics associated with the asset. Each of the metrics includes time series data. The method further involves detecting that one of the metrics is a counter. The detection involves seasonally differencing the metric, obtaining a regression line by performing a linear regression on the metric, and determining that an angle of the regression line exceeds a predetermined threshold angle. The method also involves training models for the metrics, the training including training a counter-specific model for the metric that is a counter. The method further involves determining, using the models after the training, at least one metric that is anomalous.