--- weight: 1 title: VictoriaMetrics Anomaly Detection Quick Start menu: docs: parent: "anomaly-detection" weight: 1 title: Quick Start aliases: - /anomaly-detection/QuickStart.html --- For service introduction visit [README](https://docs.victoriametrics.com/anomaly-detection/) page and [Overview](https://docs.victoriametrics.com/anomaly-detection/overview/) 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) > **Note**: Starting from [v1.13.0](https://docs.victoriametrics.com/anomaly-detection/changelog/#v1130) there is a mode to keep anomaly detection models on host filesystem after `fit` stage (instead of keeping them in-memory by default); This may lead to **noticeable reduction of RAM used** on bigger setups. See instructions [here](https://docs.victoriametrics.com/anomaly-detection/faq/#on-disk-mode). > **Note**: Starting from [v1.16.0](https://docs.victoriametrics.com/anomaly-detection/changelog/#v1160), a similar optimization is available for data read from VictoriaMetrics TSDB. See instructions [here](https://docs.victoriametrics.com/anomaly-detection/faq/#on-disk-mode). ### 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:v1.16.3 ``` 2. (Optional step) tag the `vmanomaly` Docker image: ```sh docker image tag victoriametrics/vmanomaly:v1.16.3 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 \ --licenseFile=/license ``` In case you found `PermissionError: [Errno 13] Permission denied:` in `vmanomaly` logs, set user/user group to 1000 in the run command above / in a docker-compose file: ```sh export YOUR_LICENSE_FILE_PATH=path/to/license/file export YOUR_CONFIG_FILE_PATH=path/to/config/file docker run -it --user 1000:1000 \ -v $YOUR_LICENSE_FILE_PATH:/license \ -v $YOUR_CONFIG_FILE_PATH:/config.yml \ vmanomaly /config.yml \ --licenseFile=/license ``` ```yaml # docker-compose file services: # ... vmanomaly: image: victoriametrics/vmanomaly:v1.16.3 volumes: $YOUR_LICENSE_FILE_PATH:/license $YOUR_CONFIG_FILE_PATH:/config.yml command: - "/config.yml" - "--licenseFile=/license" # ... ``` For a complete docker-compose example please refer to [our alerting guide](https://docs.victoriametrics.com/anomaly-detection/guides/guide-vmanomaly-vmalert/), chapter [docker-compose](https://docs.victoriametrics.com/anomaly-detection/guides/guide-vmanomaly-vmalert/#docker-compose) See also: - Verify the license online OR offline. See the details [here](https://docs.victoriametrics.com/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 schedulers: 2h_1m: # https://docs.victoriametrics.com/anomaly-detection/components/scheduler/#periodic-scheduler class: 'periodic' infer_every: '1m' fit_every: '2h' fit_window: '2w' models: # https://docs.victoriametrics.com/anomaly-detection/components/models/#prophet prophet_model: class: "prophet" # or "model.prophet.ProphetModel" until v1.13.0 args: interval_width: 0.98 reader: # https://docs.victoriametrics.com/anomaly-detection/components/reader/#vm-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: # https://docs.victoriametrics.com/anomaly-detection/components/writer/#vm-writer datasource_url: "http://victoriametrics:8428/" # [YOUR_DATASOURCE_URL] ``` Next steps: - Define how often to run and make inferences in the [scheduler](https://docs.victoriametrics.com/anomaly-detection/components/scheduler/) section of a config file. - Setup the datasource to read data from in the [reader](https://docs.victoriametrics.com/anomaly-detection/components/reader/) section. - Specify where and how to store anomaly detection metrics in the [writer](https://docs.victoriametrics.com/anomaly-detection/components/writer/) section. - Configure built-in models parameters according to your needs in the [models](https://docs.victoriametrics.com/anomaly-detection/components/models/) section. - Integrate your [custom models](https://docs.victoriametrics.com/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](https://docs.victoriametrics.com/anomaly-detection/guides/guide-vmanomaly-vmalert/) - [FAQ](https://docs.victoriametrics.com/anomaly-detection/faq/) - [Changelog](https://docs.victoriametrics.com/anomaly-detection/changelog/) - [Anomaly Detection Blog](https://victoriametrics.com/blog/tags/anomaly-detection/)