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| -rw-r--r-- | health/health.d/ml.conf | 36 |
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diff --git a/health/health.d/ml.conf b/health/health.d/ml.conf new file mode 100644 index 000000000..9bcc81e76 --- /dev/null +++ b/health/health.d/ml.conf @@ -0,0 +1,36 @@ +# 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
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