detecting-anomalies
Detect anomalies in metrics and time-series data using OPAL statistical methods. Use when you need to identify unusual patterns, spikes, drops, or outliers in observability data. Covers statistical outlier detection (Z-score, IQR), threshold-based alerts, rate-of-change detection with window functions, and moving average baselines. Choose pattern based on data distribution and anomaly type.
Installation and usage
Detect anomalies in metrics and time-series data using OPAL statistical methods. Use when you need to identify unusual patterns, spikes, drops, or outliers in observability data. Covers statistical outlier detection (Z-score, IQR), threshold-based alerts, rate-of-change detection with window functions, and moving average baselines. Choose pattern based on data distribution and anomaly type.
安裝後，您可以透過在終端機執行以下指令來使用此技能：
skills use detecting-anomalies