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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