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+# below are some examples of using the `anomaly-bit` option to define alerts based on anomaly
+# rates as opposed to raw metric values. You can read more about the anomaly-bit and Netdata's
+# native anomaly detection here:
+# https://learn.netdata.cloud/docs/configure/machine-learning#anomaly-bit---100--anomalous-0--normal
+
+# examples below are commented, you would need to uncomment and adjust as desired to enable them.
+
+# alert per dimension example
+# if anomaly rate is between 5-20% then warning (pick your own threshold that works best via tial and error).
+# if anomaly rate is above 20% then critical (pick your own threshold that works best via tial and error).
+# template: ml_5min_cpu_dims
+# on: system.cpu
+# os: linux
+# hosts: *
+# lookup: average -5m anomaly-bit foreach *
+# calc: $this
+# units: %
+# every: 30s
+# warn: $this > (($status >= $WARNING) ? (5) : (20))
+# crit: $this > (($status == $CRITICAL) ? (20) : (100))
+# info: rolling 5min anomaly rate for each system.cpu dimension
+
+# alert per chart example
+# if anomaly rate is between 5-20% then warning (pick your own threshold that works best via tial and error).
+# if anomaly rate is above 20% then critical (pick your own threshold that works best via tial and error).
+# template: ml_5min_cpu_chart
+# on: system.cpu
+# os: linux
+# hosts: *
+# lookup: average -5m anomaly-bit of *
+# calc: $this
+# units: %
+# every: 30s
+# warn: $this > (($status >= $WARNING) ? (5) : (20))
+# crit: $this > (($status == $CRITICAL) ? (20) : (100))
+# info: rolling 5min anomaly rate for system.cpu chart \ No newline at end of file