--- sort: 1 weight: 1 title: VictoriaMetrics Anomaly Detection Quick Start menu: docs: parent: "anomaly-detection" weight: 1 title: Quick Start aliases: - /anomaly-detection/QuickStart.html --- # VictoriaMetrics Anomaly Detection Quick Start For service introduction visit [README](/anomaly-detection/) page and [Overview](/anomaly-detection/overview.html) of how `vmanomaly` works. ## How to install and run vmanomaly > To run `vmanomaly`, you need to have VictoriaMetrics Enterprise license. You can get a trial license key [**here**](https://victoriametrics.com/products/enterprise/trial/). The following options are available: - [To run Docker image](#docker) - [To run in Kubernetes with Helm charts](#kubernetes-with-helm-charts) ### Docker > To run `vmanomaly`, you need to have VictoriaMetrics Enterprise license. You can get a trial license key [**here**](https://victoriametrics.com/products/enterprise/trial/). Below are the steps to get `vmanomaly` up and running inside a Docker container: 1. Pull Docker image: ```sh docker pull victoriametrics/vmanomaly:latest ``` 2. (Optional step) tag the `vmanomaly` Docker image: ```sh docker image tag victoriametrics/vmanomaly:latest vmanomaly ``` 3. Start the `vmanomaly` Docker container with a *license file*, use the command below. **Make sure to replace `YOUR_LICENSE_FILE_PATH`, and `YOUR_CONFIG_FILE_PATH` with your specific details**: ```sh export YOUR_LICENSE_FILE_PATH=path/to/license/file export YOUR_CONFIG_FILE_PATH=path/to/config/file docker run -it -v $YOUR_LICENSE_FILE_PATH:/license \ -v $YOUR_CONFIG_FILE_PATH:/config.yml \ vmanomaly /config.yml \ --license-file=/license ``` See also: - You can verify licence online and offline. See the details [here](/anomaly-detection/overview/#licensing). - [How to configure `vmanomaly`](#how-to-configure-vmanomaly) ### Kubernetes with Helm charts > To run `vmanomaly`, you need to have VictoriaMetrics Enterprise license. You can get a trial license key [**here**](https://victoriametrics.com/products/enterprise/trial/). You can run `vmanomaly` in Kubernetes environment with [these Helm charts](https://github.com/VictoriaMetrics/helm-charts/blob/master/charts/victoria-metrics-anomaly/README.md). ## How to configure vmanomaly To run `vmanomaly` you need to set up configuration file in `yaml` format. 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. ```yaml scheduler: infer_every: "1m" fit_every: "2h" fit_window: "14d" models: prophet_model: class: "model.prophet.ProphetModel" args: interval_width: 0.98 reader: datasource_url: "http://victoriametrics:8428/" # [YOUR_DATASOURCE_URL] sampling_period: "1m" queries: # define your queries with MetricsQL - https://docs.victoriametrics.com/metricsql/ cache: "sum(rate(vm_cache_entries))" writer: datasource_url: "http://victoriametrics:8428/" # [YOUR_DATASOURCE_URL] ``` Next steps: - Define how often to run and make inferences in the [scheduler](/anomaly-detection/components/scheduler/) section of a config file. - Setup the datasource to read data from in the [reader](/anomaly-detection/components/reader/) section. - Specify where and how to store anomaly detection metrics in the [writer](/anomaly-detection/components/writer/) section. - Configure built-in models parameters according to your needs in the [models](/anomaly-detection/components/models/) section. - Integrate your [custom models](/anomaly-detection/components/models/#custom-model-guide) with `vmanomaly`. - Define queries for input data using [MetricsQL](https://docs.victoriametrics.com/metricsql/). ## Check also Here are other materials that you might find useful: - [Guide: Anomaly Detection and Alerting Setup](/anomaly-detection/guides/guide-vmanomaly-vmalert/) - [FAQ](/anomaly-detection/faq/) - [Changelog](/anomaly-detection/changelog/) - [Anomaly Detection Blog](https://victoriametrics.com/blog/tags/anomaly-detection/)