Skip to content

Error Tracking

The Error Tracking Explorer centrally analyzes error data from APM. Through it, you can:

  • View error historical trends: Observe the frequency change curve of specific error types or sources over time through charts like Top List, Time Series, etc.

  • Analyze error distribution: Quickly locate high-frequency error sources, such as service error rates, resource endpoint error rates.

  • Aggregate similar errors: Automatically group error requests with the same exception stack or similar error characteristics to avoid repeatedly viewing single traces.

  • ...

Data Display

The Error Tracking Explorer provides various professional analysis views based on lists and charts.

List

Displays detailed records and aggregated results of APM errors within the current workspace, including occurrence time, error type, error message, associated service and resource, etc.

In list mode, two analysis modes are provided:

All Errors

Records all Spans marked as errors (status=error) and containing an error type (error_type), ultimately viewing all error records that meet the conditions.

Data Details

In the Error Tracking Explorer, click on any error to view its trace details, including service, error type, content, distribution chart, details, trace details, extended attributes, and associated LOG, HOST, NETWORK, etc.

In the error distribution chart on the error details page, based on the error_message and error_type fields, error traces with high similarity are aggregated and counted. The time interval is automatically selected based on the time range, presenting the error distribution trend.

Displays error detail information.

Displays field information under the service of the current error trace.

Obsy AI AI Error Analysis

Guance provides the capability to parse error data with one click. It utilizes large models to automatically extract key information from the data, combines online search engines and operation knowledge bases, quickly analyzes possible fault causes, and provides preliminary solutions.

  1. Click on a single data entry to expand the details page.
  2. Click the "Obsy AI AI Error Analysis" button in the upper right corner.
  3. Anomaly analysis starts automatically.

View Trace

On the details page, click the "View Trace" button in the upper right corner. The system will display the complete call trace associated with this error in a new browser tab.

Data Export

Click the "Export" button to export the current trace details as a JSON file.

Pattern

Automatically groups similar errors and identifies high-frequency patterns, displaying the top 10,000 error Span information within the selected time range. Based on the pattern fields, similarity calculations are performed on error trace data to extract common patterns, helping to quickly discover abnormal traces and locate problems.

By default, aggregation is based on the error_message field. Custom pattern fields can be input, with a maximum of 3.

Pattern Details

In the Pattern list, click on any error to view all associated traces.

On the associated traces page, you can sort the number of documents in ascending/descending order (default is descending).

Clicking on a specific data entry in the associated traces again will enter the details page. You can perform the following operations:

  • View the host and service where the error occurred, error distribution, and other information.
  • Click the icon in the upper right corner of the details page to export the current data.
  • Perform AI Intelligent Analysis on the current error details.
  • Click to jump to the trace associated with the current error details.

Charts

Based on the count, last, first, count_distinct operation modes, data is filtered under by conditions and presented in chart form. Includes the following charts, selectable as needed:

  • Top List
  • Time Series
  • Pie Chart
  • Treemap
  • Grouped Table Chart

Feedback

Is this page helpful? ×