# Behavioral analysis Metrics and monitoring are the two analysis layers of the platform. They work together: metrics transform events into time series, and monitors observe those series to detect behaviors outside the expected range. ## How they relate Everything begins with the events your operation sends. From those, you configure a **metric** to aggregate that data over time — counting occurrences, summing values, calculating rates. The metric is the lens through which you see what is happening. With the metric in place, you configure a **monitor** to watch it automatically. The monitor runs at regular intervals and opens an alert when it detects something outside the normal pattern — either by a manual rule you defined, or by an anomaly identified through machine learning. To track your metrics visually, organize them into [dashboards](/en/behavioral/dashboards/): customizable panels that bring together, on a single screen, what matters most to your operation.

Event → Metric → Monitor → Alert

Metric

type:   "transaction"
agg:    count
dim:    "status"
filter: "BRL"

time series

observes

Monitor

metric:    "transaction"
interval: 5min
rule:     anomaly
alert:    ↑ spike

continuous surveillance

## When to use each Use **metrics** to answer questions about the past and present: how many transactions per hour? What is the average approved value? The metric is a tool for observation and analysis. Use **monitors** when you need to be automatically notified about relevant changes: a sharp drop in volume, an abnormal increase in declines, a value that exceeded a critical threshold. Monitoring is the continuous surveillance layer. ## Table of contents - [Metrics](/en/behavioral/metrics/index.html.md) - [Dashboards](/en/behavioral/dashboards/index.html.md) - [Monitors](/en/behavioral/monitors/index.html.md) - [Alerts](/en/behavioral/alerts/index.html.md) - [Notifications](/en/behavioral/notifications/index.html.md)