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The Monitoring and Tracing section in Lyzr Studio provides real-time insights into agent usage, performance, and credit consumption. By standardizing traces with OpenTelemetry, we provide improved log quality, advanced filtering, and high-fidelity reporting to help teams maintain reliability at scale.

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🔹 Monitoring Overview

Monitoring offers a dashboard view of agent activity and system health. With the move to OpenTelemetry standardization, the system provides higher-quality logs and more granular data points.
  • OpenTelemetry Standardization: Improved log quality, filtering, and reporting accuracy.
  • Administrative Oversight: Owners and Admins now have access to all users’ data for centralized monitoring.
  • Trace-level Status: Immediate visibility into success/failure status to identify and fix issues faster.
Monitoring Dashboard

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🔹 Analytics Dashboard

The Analytics tab provides high-level visualization of agent-wise usage metrics. We have introduced new charts to help you deeply analyze traces and uncover operational insights.

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Key Metrics

  • Total Credits: Aggregate credits spent, including average cost per trace.
  • Avg Latency: Mean response time of agents (in seconds).
  • Reliability Score: Real-time percentage of successful executions (Error rate: 0.00%).
  • Token Efficiency: Tracks average tokens used per trace to optimize LLM costs.

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Performance Charts

  • Error Rate: A dedicated timeline visualizing the percentage of failures over time.
  • Token Usage: Breakdown of input and output tokens to analyze model consumption.
  • Latency Trends: Tracks both Average and P95 latency to identify performance bottlenecks.
  • Credits Consumed: Daily credit usage trends for budget management.
Analytics Trends

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🔹 Tracing

Switch to the Traces tab to see execution-level details of agents with fine-grained event logs.

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Root Traces

The traces view allows you to inspect every individual execution:
  • Trace ID: Unique identifier for specific run tracking.
  • Duration: Precise execution time for each request.
  • Cost & Tokens: Real-time credit and token consumption for the specific trace.
  • Start Time: Timestamp of execution.
Root Traces

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Enhanced Filtering

Use the Filter Analytics sidebar to drill down into data by:
  • Date Range: Select specific windows (max 31 days).
  • Agent Name: Filter by specific AI agents.
  • User: Admins can filter by specific team members.
  • Session ID: Isolate traces belonging to a single session.
Filter Analytics

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🔹 Debugging & Detailed Logs

Clicking any trace opens a deep-dive view into the agent’s internal operations, which is essential for validating tool calls and responses.

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Trace Timeline

  • Operation Waterfall: See the sequence of events from Session start to Agent Orchestration and Generate AI Response.
  • Span Duration: Identify exactly which step (e.g., a specific tool call) is causing latency.
Trace Timeline

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Detailed Metadata & Logs

  • Metadata: Access Agent ID, Org ID, User ID, and specific LLM model details (e.g., gpt-5-mini).
  • Execution Logs: Expand individual operations to view raw logs and internal event data.
Detailed Logs