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Tracea: Self-hosted monitoring and debugging tool for AI agents with automatic RCA and team memory

By

Darshan Nere

1mo ago· 1 min readenProduct

Summary

Tracea is a self-hosted monitoring and debugging tool for AI agents, similar to Datadog but purpose-built for agent workflows. It captures all tool calls, LLM responses, and cost data; provides automatic root cause analysis (RCA) for failures; uses YAML-based detection rules to catch errors before production; and features a "Company Brain" that turns session data into reusable team knowledge. It deploys via a single Docker command with data staying entirely on-premises.

Key quotes

· 5 pulled
Agents fail silently. You fire one off, it runs, nothing comes back - no trace, no cost data, no idea which call broke.
Tracea captures every tool call, LLM response, and cost spike.
Automatic RCA tells you exactly why it failed.
Self-hosted. One Docker command. No data leaves your network.
Company Brain turns every session into team memory - agents start smarter each run.
Snippet from the RSS feed
Agents fail silently. You fire one off, it runs, nothing comes back - no trace, no cost data, no idea which call broke. Tracea captures every tool call, LLM response, and cost spike. Automatic RCA tells you exactly why it failed. YAML detection rules catc

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