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- Added self-monitoring guide for `vmanomaly`. - Added cross-referencing on other pages. - Slight improvements in wording on related pages - Update references to v1.18.4 - [x] publish Grafana dashboard to https://grafana.com/orgs/victoriametrics/dashboards: https://grafana.com/grafana/dashboards/22337-victoriametrics-vmanomaly/ @AndrewChubatiuk , JFYI if it somehow impacts your work on supporting `vmanomaly` in operator. The following checks are **mandatory**: - [x] My change adheres [VictoriaMetrics contributing guidelines](https://docs.victoriametrics.com/contributing/). |
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Overview.md | ||
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Presets.md | ||
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QuickStart.md | ||
README.md | ||
Self-monitoring.md | ||
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vmanomaly-prophet-example.webp |
In the dynamic and complex world of system monitoring, VictoriaMetrics Anomaly Detection (or shortly, vmanomaly
), being a part of our Enterprise offering, stands as a pivotal tool for achieving advanced observability. It empowers SREs and DevOps teams by automating the identification of 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, it enables teams to spot and address potential issues faster, ensuring system reliability and operational efficiency.
Practical Guides and Installation
Get started with VictoriaMetrics Anomaly Detection efficiently by following our guides and installation options:
-
Quickstart: Learn how to quickly set up
vmanomaly
by following the Quickstart Guide. -
Overview: Understand the architecture and operation of the
vmanomaly
service here. -
Integration: Integrate anomaly detection into your existing observability stack. Find detailed steps here.
-
Anomaly Detection Presets: Enable anomaly detection on predefined sets of metrics that require frequent static threshold changes for alerting. Learn more here.
-
Installation Options: Choose the installation method that best fits your infrastructure:
- Docker Installation: Ideal for containerized environments. Follow the Docker Installation Guide.
- Helm Chart Installation: Recommended for Kubernetes deployments. See our Helm charts.
-
Self-Monitoring: Ensure
vmanomaly
is functioning optimally with built-in self-monitoring capabilities. Use the provided Grafana dashboards and alerting rules to track service health and operational metrics. Find the complete docs here.
Note
: starting from v1.5.0
vmanomaly
requires a license key to run. You can obtain a trial license key here.
Key Components
Explore the integral components that configure VictoriaMetrics Anomaly Detection:
Deep Dive into Anomaly Detection
Enhance your knowledge with our handbook on Anomaly Detection & Root Cause Analysis and stay updated:
- Anomaly Detection Handbook
- Follow the
#anomaly-detection
tag in our blog
Product Updates
Stay up-to-date with the latest improvements and features in VictoriaMetrics Anomaly Detection by following our blog post series.
Frequently Asked Questions (FAQ)
Got questions about VictoriaMetrics Anomaly Detection? Chances are, we've got the answers ready for you.
Dive into our FAQ section to find responses to common questions.
Get in Touch
We are eager to connect with you and adapt our solutions to your specific needs. Here's how you can engage with us:
- Book a Demo to discover what our product can do.
- Interested in exploring our Enterprise features, including Anomaly Detection? Request your trial license today and take the first step towards advanced system observability.
Our CHANGELOG is just a click away, keeping you informed about the latest updates and enhancements.