information captured in trace - unix1998/technical_notes GitHub Wiki

Trace_id is a crucial element for visualizing application traces, and the specific information you collect depends on your goal (monitoring public visits to your internal application). Here's a breakdown of typical information captured in traces and visualized in platforms like Grafana and Datadog dashboards:

Information Captured in Traces:

  • Trace ID: A unique identifier for the entire trace, allowing you to follow the complete path of a request across your application and external services.
  • Span Information: Each step within the trace is represented by a "span." Information collected for each span could include:
    • Span Name: Descriptive name of the operation performed (e.g., "Database Query," "API call to external service").
    • Start/End Timestamps: Measures the duration of each step, helping identify performance bottlenecks.
    • Service Name: Identifies the application component or service involved in the span.
    • Tags and Annotations: Additional metadata associated with the span, such as HTTP status code for API calls or database query parameters.
  • Error Information: Traces can capture and link error messages with specific spans, aiding in pinpointing the source of issues.

Monitoring Public Visits (Internal Application):

Since you want to monitor public visits, here are some specific details to capture and visualize:

  • Client Information:
    • IP Address: Can give a general idea of the visitor's location.
    • User Agent: Identifies the browser or device used to access your application.
  • Request Information:
    • HTTP Method: (GET, POST, etc.) indicates the type of request made.
    • URL Path: Shows the specific page or resource requested.
    • Request Parameters: May reveal information about user actions or searches.
  • Application Response:
    • HTTP Status Code: Indicates success (200) or error (404, 500) response.
    • Response Time: Measures how long your application took to respond to the request.

Visualization Platforms:

Platforms like Grafana and Datadog dashboards allow you to visualize this trace information in various formats:

  • Flame Graphs: Visually depict the trace as a tree, showing the duration of each span and their hierarchical relationships.
  • Time Series Graphs: Can track metrics like request count, response time, and error rates over time.
  • Tables: Provide detailed information for each trace or span, allowing for filtering and analysis.

By collecting and visualizing this information, you can gain valuable insights into how users interact with your internal application, identify performance bottlenecks, and debug potential issues more effectively.

Additional Tips:

  • Privacy Considerations: Ensure you comply with relevant privacy regulations when collecting and storing user data. Consider anonymizing IP addresses if necessary.
  • Focus on Relevant Data: Capture information that helps you achieve your monitoring goals. Avoid overwhelming dashboards with excessive detail.
  • Correlate Traces with Metrics: Combine trace data with application metrics (CPU, memory) to understand how application performance impacts user experience.

By utilizing trace information effectively, you can optimize your internal application for a smooth user experience even for public visitors.