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Diffstat (limited to 'docs/guides/monitor/anomaly-detection.md')
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1 files changed, 10 insertions, 10 deletions
diff --git a/docs/guides/monitor/anomaly-detection.md b/docs/guides/monitor/anomaly-detection.md index c0a00ef34..bc19a4f28 100644 --- a/docs/guides/monitor/anomaly-detection.md +++ b/docs/guides/monitor/anomaly-detection.md @@ -15,7 +15,7 @@ learn_rel_path: "Operations" As of [`v1.32.0`](https://github.com/netdata/netdata/releases/tag/v1.32.0), Netdata comes with some ML powered [anomaly detection](https://en.wikipedia.org/wiki/Anomaly_detection) capabilities built into it and available to use out of the box, with zero configuration required (ML was enabled by default in `v1.35.0-29-nightly` in [this PR](https://github.com/netdata/netdata/pull/13158), previously it required a one line config change). -This means that in addition to collecting raw value metrics, the Netdata agent will also produce an [`anomaly-bit`](https://github.com/netdata/netdata/blob/master/ml/README.md#anomaly-bit---100--anomalous-0--normal) every second which will be `100` when recent raw metric values are considered anomalous by Netdata and `0` when they look normal. Once we aggregate beyond one second intervals this aggregated `anomaly-bit` becomes an ["anomaly rate"](https://github.com/netdata/netdata/blob/master/ml/README.md#anomaly-rate---averageanomaly-bit). +This means that in addition to collecting raw value metrics, the Netdata agent will also produce an [`anomaly-bit`](https://github.com/netdata/netdata/blob/master/src/ml/README.md#anomaly-bit---100--anomalous-0--normal) every second which will be `100` when recent raw metric values are considered anomalous by Netdata and `0` when they look normal. Once we aggregate beyond one second intervals this aggregated `anomaly-bit` becomes an ["anomaly rate"](https://github.com/netdata/netdata/blob/master/src/ml/README.md#anomaly-rate---averageanomaly-bit). To be as concrete as possible, the below api call shows how to access the raw anomaly bit of the `system.cpu` chart from the [london.my-netdata.io](https://london.my-netdata.io) Netdata demo server. Passing `options=anomaly-bit` returns the anomaly bit instead of the raw metric value. @@ -23,19 +23,19 @@ To be as concrete as possible, the below api call shows how to access the raw an https://london.my-netdata.io/api/v1/data?chart=system.cpu&options=anomaly-bit ``` -If we aggregate the above to just 1 point by adding `points=1` we get an "[Anomaly Rate](https://github.com/netdata/netdata/blob/master/ml/README.md#anomaly-rate---averageanomaly-bit)": +If we aggregate the above to just 1 point by adding `points=1` we get an "[Anomaly Rate](https://github.com/netdata/netdata/blob/master/src/ml/README.md#anomaly-rate---averageanomaly-bit)": ``` https://london.my-netdata.io/api/v1/data?chart=system.cpu&options=anomaly-bit&points=1 ``` -The fundamentals of Netdata's anomaly detection approach and implementation are covered in lots more detail in the [agent ML documentation](https://github.com/netdata/netdata/blob/master/ml/README.md). +The fundamentals of Netdata's anomaly detection approach and implementation are covered in lots more detail in the [agent ML documentation](https://github.com/netdata/netdata/blob/master/src/ml/README.md). This guide will explain how to get started using these ML based anomaly detection capabilities within Netdata. ## Anomaly Advisor -The [Anomaly Advisor](https://github.com/netdata/netdata/blob/master/docs/cloud/insights/anomaly-advisor.md) is the flagship anomaly detection feature within Netdata. In the "Anomalies" tab of Netdata you will see an overall "Anomaly Rate" chart that aggregates node level anomaly rate for all nodes in a space. The aim of this chart is to make it easy to quickly spot periods of time where the overall "[node anomaly rate](https://github.com/netdata/netdata/blob/master/ml/README.md#node-anomaly-rate)" is elevated in some unusual way and for what node or nodes this relates to. +The [Anomaly Advisor](https://github.com/netdata/netdata/blob/master/docs/cloud/insights/anomaly-advisor.md) is the flagship anomaly detection feature within Netdata. In the "Anomalies" tab of Netdata you will see an overall "Anomaly Rate" chart that aggregates node level anomaly rate for all nodes in a space. The aim of this chart is to make it easy to quickly spot periods of time where the overall "[node anomaly rate](https://github.com/netdata/netdata/blob/master/src/ml/README.md#node-anomaly-rate)" is elevated in some unusual way and for what node or nodes this relates to.  @@ -53,20 +53,20 @@ Pressing the anomalies icon (next to the information icon in the chart header) w ## Anomaly Rate Based Alerts -It is possible to use the `anomaly-bit` when defining traditional Alerts within netdata. The `anomaly-bit` is just another `options` parameter that can be passed as part of an [alert line lookup](https://github.com/netdata/netdata/blob/master/docs/configure/start-stop-restart.md#alert-line-lookup). +It is possible to use the `anomaly-bit` when defining traditional Alerts within netdata. The `anomaly-bit` is just another `options` parameter that can be passed as part of an alert line lookup. You can see some example ML based alert configurations below: -- [Anomaly rate based CPU dimensions alert](https://github.com/netdata/netdata/blob/master/health/REFERENCE.md#example-8---anomaly-rate-based-cpu-dimensions-alert) -- [Anomaly rate based CPU chart alert](https://github.com/netdata/netdata/blob/master/health/REFERENCE.md#example-9---anomaly-rate-based-cpu-chart-alert) -- [Anomaly rate based node level alert](https://github.com/netdata/netdata/blob/master/health/REFERENCE.md#example-10---anomaly-rate-based-node-level-alert) -- More examples in the [`/health/health.d/ml.conf`](https://github.com/netdata/netdata/blob/master/health/health.d/ml.conf) file that ships with the agent. +- [Anomaly rate based CPU dimensions alert](https://github.com/netdata/netdata/blob/master/src/health/REFERENCE.md#example-8---anomaly-rate-based-cpu-dimensions-alert) +- [Anomaly rate based CPU chart alert](https://github.com/netdata/netdata/blob/master/src/health/REFERENCE.md#example-9---anomaly-rate-based-cpu-chart-alert) +- [Anomaly rate based node level alert](https://github.com/netdata/netdata/blob/master/src/health/REFERENCE.md#example-10---anomaly-rate-based-node-level-alert) +- More examples in the [`/health/health.d/ml.conf`](https://github.com/netdata/netdata/blob/master/src/health/health.d/ml.conf) file that ships with the agent. ## Learn More Check out the resources below to learn more about how Netdata is approaching ML: -- [Agent ML documentation](https://github.com/netdata/netdata/blob/master/ml/README.md). +- [Agent ML documentation](https://github.com/netdata/netdata/blob/master/src/ml/README.md). - [Anomaly Advisor documentation](https://github.com/netdata/netdata/blob/master/docs/cloud/insights/anomaly-advisor.md). - [Metric Correlations documentation](https://github.com/netdata/netdata/blob/master/docs/cloud/insights/metric-correlations.md). - Anomaly Advisor [launch blog post](https://www.netdata.cloud/blog/introducing-anomaly-advisor-unsupervised-anomaly-detection-in-netdata/). |