Error Tracking¶

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

• View error history trends: Observe the frequency change curves of specific error types or sources over time through charts like Top Lists and Time Series.

• 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

• Pattern Analysis

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 criteria.

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 information such as logs, hosts, and network.

Obsy AI Error Analysis¶

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

1. Click on a single data record to expand the details page;
2. Click "Obsy AI Error Analysis" 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 open 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 Analysis¶

Automatically groups similar errors and identifies high-frequency patterns, displaying the top 10,000 error Spans within the selected time range. Based on clustering fields, it calculates the similarity of error trace data, extracts common patterns, and helps quickly discover abnormal traces and locate problems.

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

Pattern Analysis Details¶

In the Pattern Analysis 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).

Click on a specific data record within the associated traces again to 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