> ## Documentation Index
> Fetch the complete documentation index at: https://docs.bronto.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Change Detection Monitors

> Detect significant spikes, drops, or shifts in metrics and other telemetry with Bronto change detection monitors that compare current values against historical data.

Change detection monitors allow you to receive alerts when the value of a query changes significantly compared to a previous point in time.
This feature is useful for catching unexpected spikes, drops, or shifts in your data trends.

## Creating a Change Detection Monitor

To create a change detection monitor:

1. Navigate to **Monitors** and select **+ New Monitor**.
2. Choose **Change Detection** as the monitor type.

From here, you will configure the data source, query conditions, and alert thresholds.

## How Change Detection Works

A change detection monitor compares two queries over time:

1. The monitor first runs a query for the current evaluation window (e.g. the last 15 minutes).
2. It then runs the same query offset by a chosen timeframe in the past (e.g. 1 hour ago).
3. The monitor computes the difference between the two query results.
4. If the difference exceeds the defined threshold, an alert notification is triggered.

## Change Types

When configuring your monitor, you can specify how the change is measured:

* **Change**: The raw difference between the current and past values.

$$
a - b
$$

* **% Change**: The percentage difference relative to the past value.

$$
\frac{(a - b)}{b} \times 100
$$

## Alert Conditions

In the **Set Alert Conditions** step, you define the threshold for triggering an alert.

The following operators are supported:

* **Above**
* **Below**
* **Above or Equal**
* **Below or Equal**

An alert will be sent if the computed change meets the specified condition.

Note: When monitoring for drops (using a **below** operator), the threshold value should usually be negative.
For example, to alert on a 50% drop in volume, set the threshold to `-50` rather than `50`.
This sends an alert notification when the percentage change falls below `-50%`, in other words, there has been a 50% drop.

## Configuration Options

When creating a change detection monitor, you’ll need to configure the following:

1. **Source Dataset** – Select the dataset(s) on which the queries will be run.
2. **Filters** – (Optional) Narrow down results by applying filters.
3. **Aggregation Function** – Define how data points are aggregated (e.g. `count`, `average`, `max`, `sum`).
4. **Change Type** – Choose between **Change** or **% Change**.
5. **Evaluation Window** – The time period over which the aggregation is calculated (N minutes, hours, days, weeks, up to maximum of 1 month).
6. **Timeframe Offset** – How far back in time the comparison query should be run (N minutes, hours, days, weeks, up to maximum of 1 month ago).

<img src="https://mintcdn.com/bronto/AMoSrWK1E1Vj09Sr/images/core-features/assets/images/change-detection-create.png?fit=max&auto=format&n=AMoSrWK1E1Vj09Sr&q=85&s=58eede41c31e71f1b8140dcfb59667db" alt="" width="766" height="812" data-path="images/core-features/assets/images/change-detection-create.png" />

This example shows the following conditions: The **% change** for the **count** of events with **response\_status:200** over the past **1 hour** compared to **4 hours ago**.

## Example Use Cases

* Detecting unusual traffic spikes compared to the same time yesterday.
* Monitoring error rates that suddenly increase compared to the previous hour.
* Tracking a drop in transaction volume relative to the past week.