# Custom evaluation delay

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## Overview[​](#overview "Direct link to Overview")

Lags in your data pipeline can cause delays in log and metric ingestion, potentially leading to false alerts. While alert conditions are evaluated in real-time, delayed data arriving later can retroactively affect whether those conditions are met.

When an alert should be triggered above a user-defined threshold, missing data may delay it or lead to an incorrect resolution. Conversely, when an alert should be triggered below a user-defined threshold, incomplete data can cause a false positive alert or delayed alert resolution.

The **Custom Evaluation Delay** feature helps mitigate this issue by shifting an alert's evaluation timeframe backward by a configurable amount. This adjustment ensures that alert conditions are evaluated against a more complete dataset, accounting for late-arriving logs or metrics.

By using Evaluation Delay, you can reduce the risk of false positives or negatives caused by real-time data fluctuations and improve the accuracy and reliability of your alerts.

## Configuration[​](#configuration "Direct link to Configuration")

1. Open the [alert creation wizard](https://docs-docusaurus.kinsta.page/user-guides/alerting/configuring-alert-definition/.md): go to **Alerts**, then select **Create alert**. You can also start from a saved query in Explore and select **Create alert**.
2. In the **Condition** step, expand **Advanced configurations**.
3. Set **Delay alert evaluation** to the time period you want the evaluator to wait for late-arriving data.

## Related resources[​](#related-resources "Direct link to Related resources")

[Configure alert definition](https://docs-docusaurus.kinsta.page/user-guides/alerting/configuring-alert-definition/.md)[Introduction to alerts](https://docs-docusaurus.kinsta.page/user-guides/alerting/introduction-to-alerts/.md)

## Next steps[​](#next-steps "Direct link to Next steps")

Adjust anomaly detection thresholds for your alerts in [Customizing anomaly detection alert sensitivity](https://docs-docusaurus.kinsta.page/user-guides/alerting/anomaly-detection-deviation-percentage/.md).