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@ -20,14 +20,14 @@ The following `tip` changes can be tested by building from the `latest` tag:
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docker pull us-docker.pkg.dev/victoriametrics-test/public/vmanomaly-trial:latest
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```
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Please find [launch instructions here](/anomaly-detection/overview.html#run-vmanomaly-docker-container).
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Please find [launch instructions here](/anomaly-detection/Overview.html#run-vmanomaly-docker-container).
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# tip
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## v1.8.0
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Released: 2024-01-15
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- FEATURE: Added Univariate [MAD (median absolute deviation)](/anomaly-detection/components/models.md#mad-median-absolute-deviation) model support.
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- FEATURE: Added Univariate [MAD (median absolute deviation)](/anomaly-detection/components/models.html#mad-median-absolute-deviation) model support.
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- IMPROVEMENT: Update Python to 3.12.1 and all the dependencies.
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- IMPROVEMENT: Don't check /health endpoint, check the real /query_range or /import endpoints directly. Users kept getting problems with /health.
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- DEPRECATION: "health_path" param is deprecated and doesn't do anything in config ([reader](/anomaly-detection/components/reader.html#vm-reader), [writer](/anomaly-detection/components/writer.html#vm-writer), [monitoring.push](/anomaly-detection/components/monitoring.html#push-config-parameters)).
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@ -9,6 +9,7 @@ menu:
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weight: 1
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aliases:
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- /anomaly-detection.html
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- /anomaly-detection/overview.html
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---
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@ -12,7 +12,7 @@ aliases:
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# Guides
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This section holds guides of how to set up and use VictoriaMetrics Anomaly Detection (or simply [`vmanomaly`](/anomaly-detection/overview.html)) service, integrating it with different observability components.
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This section holds guides of how to set up and use VictoriaMetrics Anomaly Detection (or simply [`vmanomaly`](/anomaly-detection/Overview.html)) service, integrating it with different observability components.
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Guides:
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@ -32,7 +32,7 @@ aliases:
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## 1. What is vmanomaly?
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*VictoriaMetrics Anomaly Detection* ([vmanomaly](https://docs.victoriametrics.com/anomaly-detection/overview.html)) is a service that continuously scans time series stored in VictoriaMetrics and detects unexpected changes within data patterns in real-time. It does so by utilizing user-configurable machine learning models.
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*VictoriaMetrics Anomaly Detection* ([vmanomaly](https://docs.victoriametrics.com/anomaly-detection/Overview.html)) is a service that continuously scans time series stored in VictoriaMetrics and detects unexpected changes within data patterns in real-time. It does so by utilizing user-configurable machine learning models.
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All the service parameters are defined in a config file.
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@ -67,8 +67,8 @@ Compared to classical alerting rules, anomaly detection is more "hands-off" and
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Practical use case is to put anomaly score generated by vmanomaly into alerting rules with some threshold.
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**In this tutorial we are going to:**
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- Configure docker-compose file with all needed services ([VictoriaMetrics Single-Node](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html), [vmalert](https://docs.victoriametrics.com/vmalert.html), [vmagent](https://docs.victoriametrics.com/vmagent.html), [Grafana](https://grafana.com/), [Node Exporter](https://prometheus.io/docs/guides/node-exporter/) and [vmanomaly](https://docs.victoriametrics.com/anomaly-detection/overview.html) ).
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- Explore configuration files for [vmanomaly](https://docs.victoriametrics.com/anomaly-detection/overview.html) and [vmalert](https://docs.victoriametrics.com/vmalert.html).
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- Configure docker-compose file with all needed services ([VictoriaMetrics Single-Node](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html), [vmalert](https://docs.victoriametrics.com/vmalert.html), [vmagent](https://docs.victoriametrics.com/vmagent.html), [Grafana](https://grafana.com/), [Node Exporter](https://prometheus.io/docs/guides/node-exporter/) and [vmanomaly](https://docs.victoriametrics.com/anomaly-detection/Overview.html) ).
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- Explore configuration files for [vmanomaly](https://docs.victoriametrics.com/anomaly-detection/Overview.html) and [vmalert](https://docs.victoriametrics.com/vmalert.html).
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- Run our own [VictoriaMetrics](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html) database with data scraped from [Node Exporter](https://prometheus.io/docs/guides/node-exporter/).
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- Explore data for analysis in [Grafana](https://grafana.com/).
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- Explore `vmanomaly` results.
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@ -271,10 +271,12 @@ scrape_configs:
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</div>
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### vmanomaly licencing
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### vmanomaly licensing
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We will utilize the license key stored locally in the file `vmanomaly_license.txt`.
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For additional licensing options, please refer to the [VictoriaMetrics Anomaly Detection documentation on licensing](https://docs.victoriametrics.com/anomaly-detection/Overview#licensing).
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We are going to use license stored locally in file `vmanomaly_license.txt` with key in it.
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You can explore other license options [here](https://docs.victoriametrics.com/anomaly-detection/overview#licensing)
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### Alertmanager setup
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