TraceRoot is an AI-powered debugging tool designed to help engineers identify and resolve production issues up to 10x faster by analyzing traces, logs, and code context. It targets developers and teams seeking to streamline their debugging workflows with intelligent assistance and flexible LLM integration.

How It Works

TraceRoot leverages AI agents to analyze distributed traces and logs, correlating them with code context to pinpoint root causes. Its flexibility allows users to integrate their own LLMs (OpenAI, Anthropic, local models), offering a customizable AI debugging experience. The system provides a specialized interface for debugging and integrates with common development tools.

Quick Start & Requirements

• TraceRoot Cloud: Sign up for a 7-day free trial.
• Self-hosting: Deploy a starter instance on Linux via Docker with a single command: /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/traceroot-ai/traceroot/HEAD/bin/deploy-starter)". This starts the UI at http://localhost:3000 and API at http://localhost:8000.
• SDKs: Python (traceroot-sdk) and JavaScript/TypeScript (traceroot-sdk-ts) are available.
• Prerequisites: Docker for self-hosting.
• Documentation: TraceRoot documentation

Highlighted Details

• AI-powered debugging interface with LLM flexibility (BYOM).
• Supports distributed tracing across multiple services.
• Integrates with GitHub, Notion, and other development tools.
• Offers both a cloud-based solution and self-hosting options.

Maintenance & Community

• Active development with links to Discord for community discussion.
• Project authors are Zecheng Zhang and Xinwei He.

Licensing & Compatibility

• The repository does not explicitly state a license in the provided README.

Limitations & Caveats

• The self-hosting deployment is described as a "starter instance," implying it may not be suitable for large-scale production without further configuration or migration to TraceRoot Cloud. The license is not specified, which could impact commercial use.