Debugging and Monitoring in AgenticGoKit

Overview

This section covers comprehensive debugging and monitoring strategies for AgenticGoKit applications. You'll learn how to troubleshoot multi-agent systems, implement effective logging, set up monitoring, and optimize performance in production environments.

Debugging multi-agent systems presents unique challenges due to their distributed nature, asynchronous execution, and complex interaction patterns. This guide provides practical tools and techniques to help you identify, diagnose, and resolve issues effectively.

What You'll Learn

• Debugging Multi-Agent Systems: Techniques for troubleshooting complex agent interactions
• Logging and Tracing: Implementing structured logging and distributed tracing
• Performance Monitoring: Setting up metrics, alerts, and performance optimization
• Production Troubleshooting: Common issues and their solutions in production environments

Prerequisites

Before diving into debugging and monitoring, you should be familiar with:

• Agent Lifecycle
• Message Passing and Event Flow
• Orchestration Patterns
• State Management

Why Debugging Multi-Agent Systems is Different

Multi-agent systems introduce several debugging challenges:

1. Concurrent Execution

• Agents may run on different threads within the same process
• State changes occur across multiple components simultaneously
• Race conditions and timing issues are more common with concurrent execution

2. Asynchronous Communication

• Events flow through the system asynchronously
• Cause and effect relationships may be separated in time
• Error propagation can be complex and delayed

3. Complex State Management

• State is shared and modified by multiple agents
• State transformations may be non-deterministic
• Debugging requires understanding the entire state flow

4. Orchestration Complexity

• Different orchestration patterns have different failure modes
• Agent interactions can create emergent behaviors
• System behavior may vary based on timing and load

Debugging Philosophy

Effective debugging of multi-agent systems requires a systematic approach:

1. Observability First

• Implement comprehensive logging before you need it
• Use structured logging with consistent formats
• Include correlation IDs to track requests across agents

2. Fail Fast and Clearly

• Validate inputs and state at agent boundaries
• Use clear, actionable error messages
• Implement circuit breakers to prevent cascade failures

3. Isolate and Reproduce

• Create minimal test cases that reproduce issues
• Use deterministic testing with controlled inputs
• Implement agent mocking for isolated testing

4. Monitor Continuously

• Set up metrics and alerts for key system behaviors
• Track performance trends over time
• Use health checks to detect issues early

Getting Started

Start with Debugging Multi-Agent Systems to learn fundamental debugging techniques, then progress through the other guides based on your specific needs.

Quick Reference

Common Debugging Commands

# List available trace sessions
agentcli list

# View execution trace for a session
agentcli trace <session-id>

# View only agent flow without state details
agentcli trace --flow-only <session-id>

# Filter trace to specific agent
agentcli trace --filter agent=<agent-name> <session-id>

# View verbose trace with full state details
agentcli trace --verbose <session-id>

# Debug trace structure
agentcli trace --debug <session-id>

# Check MCP servers and tools
agentcli mcp servers
agentcli mcp tools

# View memory system status
agentcli memory --stats

# Check cache statistics
agentcli cache stats

Configuration in agentflow.toml

[logging]
level = "debug"  # debug, info, warn, error
format = "json"  # json or text

[agent_flow]
name = "my-agent-system"
version = "1.0.0"

# Enable tracing (traces are saved as .trace.json files)
[runtime]
max_concurrent_agents = 10

Key Metrics to Monitor

• Agent Response Time: Time from event receipt to result
• Error Rate: Percentage of failed agent executions
• Queue Depth: Number of pending events in orchestrator
• Memory Usage: Memory consumption per agent
• Tool Call Latency: Time for external tool executions