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

# A/B Testing

> Split production traffic between two policy versions to compare their performance.

## What is A/B Testing?

A/B testing lets you route a percentage of live traffic to a **test version** while the rest continues to the **current live version**. Both versions produce execution logs, so you can compare their performance with real data before fully switching.

## Prerequisites

Before starting an A/B test, you need:

* A policy group with a **currently deployed** (live) version
* A **test version** that has been published (ACTIVE status)
* Both versions must belong to the same policy group

## Starting an A/B Test

### Console

Navigate to the policy group → click **Start A/B Test** → select the test version → set the traffic percentage.

### CLI

```bash theme={null}
lexq groups ab-test start \
  --group-id <groupId> \
  --version-id <testVersionId> \
  --traffic-rate 10
```

The `--traffic-rate` is the percentage (1–99) of traffic routed to the test version. The remaining traffic stays on the live version.

## Monitoring Results

While the A/B test is running, both versions generate execution logs. Compare them using:

```bash theme={null}
lexq history stats --group-id <groupId>
```

Check success rates, match rates, latency, and output variable distributions across both versions.

## Adjusting Traffic

Gradually increase the test version's traffic as you gain confidence:

```bash theme={null}
lexq groups ab-test adjust --group-id <groupId> --traffic-rate 30
lexq groups ab-test adjust --group-id <groupId> --traffic-rate 50
```

## Stopping an A/B Test

```bash theme={null}
lexq groups ab-test stop --group-id <groupId>
lexq groups ab-test stop --group-id <groupId> --force
```

Stopping reverts all traffic to the live version. The test version remains ACTIVE but no longer receives traffic.

## Typical Workflow

```
1. Create a new DRAFT version with rule changes
2. Dry-run to validate the changes
3. Publish the new version (DRAFT → ACTIVE)
4. Start A/B test at 10% traffic
5. Monitor execution logs and compare metrics
6. Gradually increase: 10% → 30% → 50%
7. If satisfied, deploy the test version as the new live version
8. Stop the A/B test
```

<Warning>
  A/B tests affect **production traffic**. Start with a low traffic percentage (5–10%) and monitor closely before scaling up.
</Warning>

## Next Steps

<CardGroup cols={2}>
  <Card title="Impact Simulation" icon="chart-bar" href="/guides/simulation">
    Test against historical data before running an A/B test.
  </Card>

  <Card title="Deployments" icon="rocket" href="/guides/deployments">
    Deploy the winning version to production.
  </Card>
</CardGroup>