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Show HN: TraceRoot – Open-source agentic debugging for distributed services

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Re: Show HN: TraceRoot – Open-source agentic debugging for distributed services

#11

Post by xinweihe »

Onawa wrote: post #10
thatrandybrown wrote: post #6

I like the idea of this and the use case, but don't love the tight coupling to openai. I'd love to see a framework for allowing BYOM.

It's been 2.5 years since ChatGPT came out, and so many projects still don't allow for easy switching of the OPEN_AI_BASE_URL or affiliated parameters. There are so many inferencing libraries that serve an OpenAI-compatible API that any new project being locked in to OpenAI only is a large red flag for me.

Thanks for the feedback! Totally hear you on the tight OpenAI coupling - we're aware and already working to make BYOM easier. Just to echo what Zecheng said earlier: broader model flexibility is definitely on the roadmap.

Appreciate you calling it out — helps us stay honest about the gaps.

Re: Show HN: TraceRoot – Open-source agentic debugging for distributed services

#12

Post by ethan_smith »

thatrandybrown wrote: post #6

I like the idea of this and the use case, but don't love the tight coupling to openai. I'd love to see a framework for allowing BYOM.

Adding model provider abstraction would significantly improve adoption, especially for organizations with specific LLM preferences or air-gapped environments that can't use OpenAI.

Re: Show HN: TraceRoot – Open-source agentic debugging for distributed services

#13

Post by lmeyerov »

I'm curious -- let's say we have claude code hooked up to MCPs for jaeger, grafana, and the usual git/gh CLIs it can use out-of-the-box, and we let claude's planner work through investigations with whatever help we give it. Would TraceRoot do anything clever wrt the AI that such as a setup wouldn't/couldn't?

(I'm asking b/c we're planning a setup that's basically that, so real question.)

Re: Show HN: TraceRoot – Open-source agentic debugging for distributed services

#15

Post by xinweihe »

ethan_smith wrote: post #12
thatrandybrown wrote: post #6

I like the idea of this and the use case, but don't love the tight coupling to openai. I'd love to see a framework for allowing BYOM.

Adding model provider abstraction would significantly improve adoption, especially for organizations with specific LLM preferences or air-gapped environments that can't use OpenAI.

Yep, you're spot on - and we're hearing this loud and clear across the thread. Model abstraction is on the roadmap, and we're already working on making BYOM smoother.

Re: Show HN: TraceRoot – Open-source agentic debugging for distributed services

#17

Post by xinweihe »

sand_9999 wrote: post #16

I can connect MCP for Datadog/NewRelic/Cloudwatch logs. Cursor or ClaudeCode would give me all that I need. Are you doing something new here?

Fair question. Here’s how TraceRoot is different.

- We don’t just stream raw logs/traces into an LLM, we build execution trees and correlate data across services and threads. That gives our agent causal context, not just pattern matching.

- It’s designed to debug real issues in production, where things are messy, not just dev or staging.

- We are aiming for automatic bug detection and remediation soon, not just copiloting, but a debugging agent that can spot regressions and trigger fixes proactively.

- We are working on persist historical incidents, fixes, and infra quirks, so the agent improves with each investigation, and doesn’t start from scratch every time.

Happy to dive deeper! Let me know if you have more questions.

Re: Show HN: TraceRoot – Open-source agentic debugging for distributed services

#18

Post by xinweihe »

lmeyerov wrote: post #13

I'm curious -- let's say we have claude code hooked up to MCPs for jaeger, grafana, and the usual git/gh CLIs it can use out-of-the-box, and we let claude's planner work through investigations with whatever help we give it. Would TraceRoot do anything clever wrt the AI that such as a setup wouldn't/couldn't? (I'm asking b/c we're planning a setup that's basically that, so real question.)

Good question! Your setup already covers a lot — but TraceRoot tries to go a bit further in a few areas:

In TraceRoot, we organize all logs, metrics, etc. around traces and build an execution tree. This structured view makes it much easier for our agent to reason through the large amount of telemetry data using context-aware optimizations. (We plan to support slack and notion integration as well.)

It’s not a one-off tool. TraceRoot is a live monitoring platform. It continuously watches what’s happening in prod. So when something breaks, the agent already has full team-visible context, not just a scratchpad session spun up in the moment.

Down the line, we're aiming for automatic bug detection and remediation - not just smarter copiloting, but proactive debugging workflows. The system also retains team-level memory of past bugs, fixes, and infra quirks, so the agent gets smarter over time.

We’ve open sourced a lot of the core. Would love to jam on this if you're up for it. Always down to trade ideas or even hack on something together!

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