Agentic Monitoring

Agentic monitoring provides specialized observability for AI agents and multi-step workflows through dedicated dashboards, metrics, and trace visualization. Unlike traditional monitoring that tracks single-shot inferences, agentic monitoring captures the complete lifecycle of autonomous agent behavior—from initial reasoning through tool execution and final response.

Dashboards & Visualization

Agentic monitoring uses a dedicated UI with Projects → Applications (instead of the legacy Projects → Models structure) designed specifically for observing agent workflows.

Agentic Dashboards

Access pre-built dashboards optimized for agentic workflows:

  • Agent Performance Overview - Monitor success rates, latency, and throughput across all agents

  • Workflow Execution Traces - Visualize complete multi-step reasoning chains from start to finish

  • Tool Usage Analytics - Track which external tools and APIs your agents are calling

  • Error & Exception Tracking - Identify where agent workflows fail and why

Trace Visualization

Every agent interaction is captured as a hierarchical trace showing:

  • Agent Steps - Each decision point in the agent's reasoning process

  • LLM Calls - All language model interactions with inputs, outputs, and metadata

  • Tool Invocations - External function calls, API requests, and data retrievals

  • Timing Information - Duration of each step to identify performance bottlenecks

  • Parent-Child Relationships - How multi-agent systems coordinate and delegate tasks

Viewing Traces:

  1. Navigate to your Application in the Fiddler UI

  2. Select a conversation or workflow from the list

  3. Click on any trace to expand the full execution tree

  4. Drill down into individual spans to see inputs, outputs, and metadata

Custom Dashboards

Create custom dashboards to monitor specific agent behaviors:

  • Combine multiple charts to track KPIs relevant to your use case

  • Filter by agent type, user segments, or time periods

  • Share dashboards with team members

  • Set up alerts based on dashboard metrics

Metrics & Analytics

Agentic monitoring provides specialized metrics that go beyond traditional model monitoring:

Agent-Specific Metrics

  • Agent Success Rate - Percentage of workflows that complete successfully

  • Tool Call Distribution - Which tools agents use most frequently

  • Reasoning Chain Length - Average number of steps per workflow

  • Agent Handoffs - How often agents delegate to other agents

  • Retry & Recovery Rate - How often agents recover from errors

Performance Metrics

  • End-to-End Latency - Total time from user request to final response

  • Per-Step Latency - Duration of individual reasoning steps, LLM calls, and tool invocations

  • Token Usage - Track LLM consumption across all agent interactions

  • API Call Volume - Monitor external tool and API usage

Quality Metrics

  • Response Accuracy - Validate agent outputs against expected results (requires ground truth)

  • Hallucination Detection - Identify when agents generate unsupported claims

  • Safety & Guardrails - Track safety violations and guardrail activations

  • User Satisfaction - Capture feedback signals from end users

Analyzing Metrics

All metrics are available in:

  • Real-time Dashboards - Monitor live agent performance

  • Historical Trends - Analyze patterns over days, weeks, or months

  • Comparative Analysis - Compare different agent versions or configurations

  • Custom Queries - Use Fiddler Query Language (FQL) for advanced analysis

Integration Options

Agentic monitoring ingests OpenTelemetry spans and traces from your agent applications. Choose the integration method that fits your framework:

LangGraph Applications

Best for: Applications built with LangGraph or LangChain

The Fiddler LangGraph SDK provides automatic instrumentation with zero code changes required.

pip install fiddler-langgraph

→ LangGraph SDK Quick Start - Get started in 15 minutes

→ LangGraph SDK Documentation - Complete integration guide

Strands Agent Framework

Best for: Applications built with Strands Agents

The Fiddler Strands SDK integrates directly with the Strands framework for seamless monitoring.

pip install fiddler-strands

→ Strands Agent SDK Quick Start - Get started in 15 minutes

→ Strands SDK Documentation - Complete integration guide

Custom Instrumentation (OpenTelemetry)

Best for: Custom agent frameworks or non-Python applications

Use OpenTelemetry directly for maximum flexibility and control.

pip install opentelemetry-api opentelemetry-sdk

→ OpenTelemetry Quick Start - Get started in 20 minutes

→ OpenTelemetry Documentation - Complete integration guide

Integration Comparison

Feature
LangGraph SDK
Strands SDK
OpenTelemetry

Automatic Instrumentation

✅ Zero code changes

✅ Native integration

❌ Manual setup

Framework Support

LangGraph, LangChain

Strands Agents

Any framework

Language Support

Python

Python

Python, Java, Go, JS, etc.

Setup Time

~15 minutes

~15 minutes

~20 minutes

Customization

Medium

Medium

High

Next Steps

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