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Logs are records of events generated by your application during execution. They capture detailed information about requests, responses, errors, and system behavior. In Trusys, logs serve as the foundation for monitoring, debugging, and evaluating application performance and security. Logs can be explored at different levels:
  • Traces – Individual log entries representing a single request or operation.
  • Sessions – Groups of related traces, often used for analyzing multi-step interactions like conversations.

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Traces

The Traces section provides a detailed, granular view of individual log entries from your monitored applications. You can view all traces for projects where monitoring is enabled. The list can be filtered by time range or application and is sorted by the most recent logs first. The list also indicates if a log has been evaluated, and if so, provides a summary of the evaluation and the span count.

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Customize Trace Columns

Tailor the trace listing view to show the information most relevant to you. You can configure which columns appear, choose from default columns, and add custom columns from trace metadata.

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Default Columns

The following columns are available by default:
  • Date – Timestamp when the trace was captured
  • Trace ID – Unique trace identifier
  • Session ID – Session the trace belongs to
  • Application – Application name
  • Req Duration – End-to-end request duration
  • Spans – Number of spans in the trace
  • Evaluation – Evaluation status indicator
  • Evaluation Summary – Pass/fail summary (e.g., “4/11 Metrics Passed”, “2/8 Categories Passed”)
  • Actions – Row actions (e.g., Details)
You can show or hide any default column.

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Add Metric Columns

Display metric results from your active TRU PULSE monitoring metrics directly in the trace listing. How to Add:
  1. Click + Add Column
  2. Select Metric Column
  3. Choose from active (enabled) metrics only
  4. The metric score/result will display for each trace
Note: Only active metrics are selectable. Disabled or retired metrics do not appear in the picker. If a metric is later disabled, it will show a “metric disabled” indicator but retain historical results.

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Add Custom Columns

Add custom columns that display values from trace metadata. How to Add:
  1. Click + Add Column
  2. Select Custom Column
  3. Enter the field path (e.g., metadata.customer.tier, metadata.region)
  4. Enter the column name (display label)
  5. Save your configuration
Field Path:
  • Use free text to specify the path within trace metadata
  • Use dot notation for nested values (e.g., metadata.customer.tier)
  • If the field is absent for a trace, the cell shows empty

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Manage Columns

Available Actions:
  • Add – Add a default or custom column to the listing
  • Disable (Hide) – Hide a column without deleting its configuration
  • Delete – Remove a custom column entirely
  • Save – Save your column configuration
Persistence:
  • Your column configuration saves automatically per user per application
  • Settings persist across sessions until you edit them
Click on any trace to view more details, including:
  • Span Hierarchy – A hierarchical view of the operations within a single request, useful for debugging and performance analysis.
  • System and Health Metadata – Additional information about the system state and health at the time the log was generated.
  • Evaluation Details – Comprehensive results of the configured functional and security evaluations performed on that specific trace. If an evaluation has not yet been performed for a trace, you will see an option to evaluate it against your application’s monitor settings.
  • Run Evaluation – If the trace is not evaluated, click on “Run evaluation” to evaluate the trace and see the trace evaluation result.

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Sessions

Sessions are primarily used for conversational logs where a session represents a group of related traces. This is particularly useful for applications that involve multi-turn conversations or extended user interactions. Key aspects of sessions:
  • Trace Grouping – A session contains multiple traces that are logically connected, typically representing a complete conversation or user journey.
  • Conversational Metrics – For conversational applications, metrics and evaluations are performed at the session level rather than individual trace level, providing insights into the overall conversation quality and performance.
  • Session-Level Analysis – View comprehensive analytics across all traces within a session to understand user interaction patterns and conversation flow.