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The Sessions view in the Netra dashboard provides a centralized place to monitor user interactions, track custom events, and analyze session-level performance metrics. This section explains how to set up session tracking in your code and how to view and analyze sessions in the dashboard.

Setting Up Session Tracking

Before viewing sessions in the dashboard, you need to set up session tracking in your application code.

Initialize the Netra SDK

Set Session Identifiers

Track specific users, sessions, and tenants with unique identifiers:

Add Custom Context Attributes

Enrich your session data with custom attributes for better analysis:

Record Custom Events

Track important business and technical events:

Propagating Session Context to Downstream Services

Netra stores the session, user, and tenant IDs as W3C baggage. To keep these identifiers away from third-party APIs such as LLM providers, the Python SDK’s httpx and requests instrumentations remove the baggage header from outbound requests by default. Trace context (traceparent and tracestate) is still sent, so distributed traces stay connected. If your own downstream services read session, user, or tenant IDs from incoming baggage, list their hosts in NETRA_PROPAGATE_BAGGAGE_HOSTS:
With this setting, a request to api.mycorp.net carries the baggage header, and a request to api.openai.com does not. See Context Propagation for matching rules and the clients this covers.
Baggage gating is available in the Python SDK only.

Viewing Sessions in the Dashboard

The Sessions dashboard displays all your application sessions with their associated traces. Each session shows key information including session ID, creation time, duration, number of traces, and total cost. Sessions dashboard

Features

  • Filter & Search: Filter sessions by date, time range, or search by session/user ID
  • Refresh Data: Manually refresh to see the latest sessions
  • View Columns: SessionId, CreatedAt, Duration, Traces, Cost, and Actions button
Click the Actions button to navigate to the trace view and inspect all traces associated with that session.

Use Cases

  • Debugging User Issues: Retrieve a specific user’s session to review all their interactions and traces
  • Cost Analysis: Identify expensive sessions by viewing total cost per session
  • Performance Monitoring: Track session duration and number of traces to monitor application behavior
  • Error Investigation: Find sessions with failed traces to diagnose issues quickly
  • User Analytics: Analyze session patterns to understand user behavior and engagement

Next Steps

  • Users - Track individual users across sessions
  • Tenants - Organize sessions by tenant for multi-tenant applications
  • Traces Overview - Deep dive into trace data within sessions
Last modified on September 30, 2026