Given a list of real-valued metrics metrics, an integer window size k, and a non-negative real threshold t, process the stream from left to right. For each index i, once at least k values are available, compute the moving average and standard deviation of the last k values. Mark metrics[i] as anomalous if abs(metrics[i] - mean) > t * std for that current window. Return a list of window averages and a list of anomaly flags for each position where a full window exists.
1 <= len(metrics) <= 10^51 <= k <= len(metrics)0 <= t <= 10^6-10^9 <= metrics[i] <= 10^9