AI Agent Monitoring 2026: Top Open Source Platforms Compared

Your AI Agent is finally up and running—it can automatically write code, search for information, call tools, and complete complex tasks. But you quickly notice a troubling issue: the Agent is like a black box, and you have no idea what it's doing behind the scenes. Is it stuck in some infinite loop? Why has this task taken 3 minutes and still isn't done? Where exactly did that huge chunk of tokens go? There's no alert when something goes wrong—you only find out when users start complaining. This sense of losing control is even more anxiety-inducing than the Agent not working at all.

💡 What You Will Learn

Your AI Agent is finally up and running—it can automatically write code, search for information, call tools, and complete complex tasks. But you quickly notice a troubling issue: the Agent is like a b

📜 Table of Contents

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• 5. Sentry AI Agent Observability
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• Summary

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5. Sentry AI Agent Observability

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# 1. Installation/Setup
# pip install openinference-instrumentation-langchain phoenix

# 2. 
from openinference_instrumentation_langchain import LangChainInstrumentor
LangChainInstrumentor().instrument()

# 3. Phoenix
import phoenix as px
session = px.launch_app()

# 4. Agent——TraceAuto/Automatic
from langgraph.graph import StateGraph
# ... Agent ...
# LLMAuto/AutomaticPhoenix UI

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Summary