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URL: https://docs.datadoghq.com/logs/error_tracking/

⇱ Error Tracking for Logs

For AI agents: A markdown version of this page is available at https://docs.datadoghq.com/logs/error_tracking.md. A documentation index is available at /llms.txt.

Error Tracking for Logs

Overview

It is critical for your system’s health to consistently monitor the errors collected by Datadog. When there are many individual error events, it becomes hard to prioritize errors for troubleshooting.

Error Tracking simplifies debugging by grouping thousands of similar errors into a single issue. An issue is an aggregation of error data that provides insights such as

  • How many users have been impacted
  • When the error first occurred
  • Which commit probably caused the error

Error Tracking enables you to:

  • Track, triage, and debug fatal errors
  • Group similar errors into issues, so that you can more easily identify important errors and reduce noise
  • Set monitors on error tracking events, such as high error volume or new issues
  • Follow issues over time to know when they first started, if they are still ongoing, and how often they occur

Take a tour of key Error Tracking features in the Error Tracking Explorer documentation. To view the Error Tracking Explorer for Logs in Datadog, navigate to Error Tracking.

Setup

Error Tracking for Logs processes properly configured error logs with stack traces.

To get started with Datadog Error Tracking for Logs, see the corresponding documentation for your framework:


Further Reading