In the dynamic and complex world of system monitoring, VictoriaMetrics Anomaly Detection, being a part of our [Enterprise offering](https://victoriametrics.com/products/enterprise/), stands as a pivotal tool for achieving advanced observability. It empowers SREs and DevOps teams by automating the intricate task of identifying abnormal behavior in time-series data. It goes beyond traditional threshold-based alerting, utilizing machine learning techniques to not only detect anomalies but also minimize false positives, thus reducing alert fatigue. By providing simplified alerting mechanisms atop of [unified anomaly scores](/anomaly-detection/components/models.html#vmanomaly-output), it enables teams to spot and address potential issues faster, ensuring system reliability and operational efficiency.
- **Integration**: Integrate anomaly detection into your observability ecosystem. Get started [**here**](/anomaly-detection/guides/guide-vmanomaly-vmalert.html).
- **Installation Options**: Select the method that aligns with your technical requirements:
- **Helm Chart Installation**: Appropriate for those using Kubernetes. See our [Helm charts](https://github.com/VictoriaMetrics/helm-charts/tree/master/charts/victoria-metrics-anomaly).
> Note: starting from [v1.5.0](./CHANGELOG.md#v150) `vmanomaly` requires a [license key](/anomaly-detection/overview#licensing) to run. You can obtain a trial license key [**here**](https://victoriametrics.com/products/enterprise/trial/index.html).
* [Book a Demo](https://calendly.com/victoriametrics-anomaly-detection) to discover what our product can do.
* Interested in exploring our [Enterprise features](https://victoriametrics.com/products/enterprise), including Anomaly Detection? [Request your trial license](https://victoriametrics.com/products/enterprise/trial/) today and take the first step towards advanced system observability.
