diff options
author | Tasos Katsoulas <tasos@netdata.cloud> | 2022-07-29 16:48:03 +0300 |
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committer | GitHub <noreply@github.com> | 2022-07-29 16:48:03 +0300 |
commit | 82649b6e78891510c92573b80bf3e721d584a325 (patch) | |
tree | def39c89727331b500ed05e77e24fde8ebeff1c3 /docs | |
parent | eabc42013682555c63df96971624b937f8a2a104 (diff) |
fix a guide so we can reference it's subsections (#13455)
Diffstat (limited to 'docs')
-rw-r--r-- | docs/guides/monitor/anomaly-detection.md | 12 |
1 files changed, 6 insertions, 6 deletions
diff --git a/docs/guides/monitor/anomaly-detection.md b/docs/guides/monitor/anomaly-detection.md index 882a8cc32c..e98c5c02e5 100644 --- a/docs/guides/monitor/anomaly-detection.md +++ b/docs/guides/monitor/anomaly-detection.md @@ -10,7 +10,7 @@ custom_edit_url: https://github.com/netdata/netdata/edit/master/docs/guides/moni -# Overview +## Overview 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). @@ -32,7 +32,7 @@ The fundamentals of Netdata's anomaly detection approach and implmentation are c This guide will explain how to get started using these ML based anomaly detection capabilities within Netdata. -# Anomaly Advisor +## Anomaly Advisor The [Anomaly Advisor](https://learn.netdata.cloud/docs/cloud/insights/anomaly-advisor) 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://learn.netdata.cloud/docs/agent/ml#node-anomaly-rate)" is evelated in some unusual way and for what node or nodes this relates to. @@ -42,7 +42,7 @@ Once an area on the Anomaly Rate chart is highlighted netdata will append a "hea ![image](https://user-images.githubusercontent.com/2178292/175929162-02c8fe69-cc4f-4cf4-9b3a-a5e559a6feca.png) -# Embedded Anomaly Rate Charts +## Embedded Anomaly Rate Charts Charts in both the [Overview](https://learn.netdata.cloud/docs/cloud/visualize/overview) and [single node dashboard](https://learn.netdata.cloud/docs/cloud/visualize/overview#jump-to-single-node-dashboards) tabs also expose the underlying anomaly rates for each dimension so users can easily see if the raw metrics are considered anomalous or not by Netdata. @@ -50,7 +50,7 @@ Pressing the anomalies icon (next to the information icon in the chart header) w ![image](https://user-images.githubusercontent.com/2178292/175933078-5dd951ff-7709-4bb9-b4be-34199afb3945.png) -# Anomaly Rate Based Alerts +## 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 [alarm line lookup](https://learn.netdata.cloud/docs/agent/health/reference#alarm-line-lookup). @@ -61,7 +61,7 @@ You can see some example ML based alert configurations below: - [Anomaly rate based node level alarm](https://learn.netdata.cloud/docs/agent/health/reference#example-10---anomaly-rate-based-node-level-alarm) - 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. -# Learn More +## Learn More Check out the resources below to learn more about how Netdata is approaching ML: @@ -72,4 +72,4 @@ Check out the resources below to learn more about how Netdata is approaching ML: - Netdata Approach to ML [blog post](https://www.netdata.cloud/blog/our-approach-to-machine-learning/). - `areal/ml` related [GitHub Discussions](https://github.com/netdata/netdata/discussions?discussions_q=label%3Aarea%2Fml). - Netdata Machine Learning Meetup [deck](https://docs.google.com/presentation/d/1rfSxktg2av2k-eMwMbjN0tXeo76KC33iBaxerYinovs/edit?usp=sharing) and [YouTube recording](https://www.youtube.com/watch?v=eJGWZHVQdNU). -- Netdata Anomaly Advisor [YouTube Playlist](https://youtube.com/playlist?list=PL-P-gAHfL2KPeUcCKmNHXC-LX-FfdO43j).
\ No newline at end of file +- Netdata Anomaly Advisor [YouTube Playlist](https://youtube.com/playlist?list=PL-P-gAHfL2KPeUcCKmNHXC-LX-FfdO43j). |