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Markdown
115 lines
No EOL
4 KiB
Markdown
---
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sort: 1
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weight: 1
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title: VictoriaMetrics Anomaly Detection Quick Start
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menu:
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docs:
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parent: "anomaly-detection"
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weight: 1
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title: Quick Start
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aliases:
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- /anomaly-detection/QuickStart.html
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---
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# VictoriaMetrics Anomaly Detection Quick Start
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For service introduction visit [README](/anomaly-detection/) page
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and [Overview](/anomaly-detection/overview.html) of how `vmanomaly` works.
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## How to install and run `vmanomaly`
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> To run `vmanomaly` you need to have VictoriaMetrics Enterprise license. You can get a trial license key [**here**](https://victoriametrics.com/products/enterprise/trial/index.html).
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The following options are available:
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- [To run Docker image](#docker-image)
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- [To run in Kubernetes with Helm charts](#helm-charts)
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### Docker
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> To run `vmanomaly` you need to have a VictoriaMetrics Enterprise [licence](https://victoriametrics.com/products/enterprise/) or request a trial [here](https://victoriametrics.com/products/enterprise/trial/index.html).
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Below are the steps to get `vmanomaly` up and running inside a Docker container:
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1. Pull Docker image:
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```sh
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docker pull victoriametrics/vmanomaly:latest
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```
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2. (Optional step) tag the `vmanomaly` Docker image:
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```sh
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docker image tag victoriametrics/vmanomaly:latest vmanomaly
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```
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3. Start the `vmanomaly` Docker container with a *license file*, use the command below.
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**Make sure to replace `YOUR_LICENSE_FILE_PATH`, and `YOUR_CONFIG_FILE_PATH` with your specific details**:
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```sh
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export YOUR_LICENSE_FILE_PATH=path/to/license/file
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export YOUR_CONFIG_FILE_PATH=path/to/config/file
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docker run -it -v $YOUR_LICENSE_FILE_PATH:/license \
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-v $YOUR_CONFIG_FILE_PATH:/config.yml \
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vmanomaly /config.yml \
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--license-file=/license
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```
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See also:
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- You can verify licence online and offline. See the details [here](/anomaly-detection/overview/#licensing).
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- [How to configure `vmanomaly`](#how-to-configure-vmanomaly)
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### Kubernetes with Helm charts
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You can run `vmanomaly` in Kubernetes environment
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with [these Helm charts](https://github.com/VictoriaMetrics/helm-charts/blob/master/charts/victoria-metrics-anomaly/README.md).
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## How to configure vmanomaly
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To run `vmanomaly` you need to set up configuration file in `yaml` format.
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Here is an example of config file that will run [Facebook Prophet](https://facebook.github.io/prophet/) model, that will be retrained every 2 hours on 14 days of previous data. It will generate inference (including `anomaly_score` metric) every 1 minute.
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```yaml
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scheduler:
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infer_every: "1m"
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fit_every: "2h"
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fit_window: "14d"
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models:
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prophet_model:
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class: "model.prophet.ProphetModel"
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args:
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interval_width: 0.98
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reader:
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datasource_url: "http://victoriametrics:8428/" # [YOUR_DATASOURCE_URL]
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sampling_period: "1m"
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queries:
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# define your queries with MetricsQL - https://docs.victoriametrics.com/metricsql/
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cache: "sum(rate(vm_cache_entries))"
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writer:
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datasource_url: "http://victoriametrics:8428/" # [YOUR_DATASOURCE_URL]
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```
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Next steps:
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- Define how often to run and make inferences in the [scheduler](/anomaly-detection/components/scheduler/) section of a config file.
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- Setup the datasource to read data from in the [reader](/anomaly-detection/components/reader/) section.
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- Specify where and how to store anomaly detection metrics in the [writer](/anomaly-detection/components/writer/) section.
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- Configure built-in models parameters according to your needs in the [models](/anomaly-detection/components/models/) section.
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- Integrate your [custom models](/anomaly-detection/components/models/#custom-model-guide) with `vmanomaly`.
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- Define queries for input data using [MetricsQL](https://docs.victoriametrics.com/metricsql/).
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## Check also
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Here are other materials that you might find useful:
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- [Guide: Anomaly Detection and Alerting Setup](/anomaly-detection/guides/guide-vmanomaly-vmalert/)
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- [FAQ](/anomaly-detection/faq/)
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- [Changelog](/anomaly-detection/changelog/)
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- [Anomaly Detection Blog](https://victoriametrics.com/blog/tags/anomaly-detection/) |