Anomify is an event detection tool for time-series data. It alerts you to changes in your metrics in real-time by learning from their behaviour so that it can identify abnormal trends.
What can I use Anomify for?
Since Anomify relies on feedback from your team to work effectively, it can be trained to detect anomalies across time-series data from any industry. It is typically used by alongside other monitoring tools as part of an observability stack.
Anomify has been used to:
- monitor the performance of IT infrastructure.
- detect payment failures in a payments service for an e-commerce store.
- monitor temperature fluctuations in solar-thermal heat pumps.
Anomaly detection analysis will start automatically once Anomify starts receiving data and you'll receive alerts when it detects significant changes in your metrics. The system performs best when it receives metric data at consistent time intervals.
How to use these docs
The Anomify workflow is split into three stages that occur in sequence:
- Getting metrics into Anomify
- Configuring Alerts
- Responding to Alerts
Dig into the sub pages in the sidebar to get started. First try adding a few test metrics using one of the 'Source:..' tutorials in the Getting metrics into Anomify section.
Note that many of the code examples relate to server metrics but they could be substituted for business metrics, IOT metrics, etc
You can interact with Anomify programmatically. All methods available to the dashboard are exposed for use.