Hey everyone! 👋 I’ve been lurking here for a bit while trying to set up proper LLM observability for my team’s project management chatbot. We’re a small remote team using Asana and Slack, and I was tasked with finding a tool to track the chatbot’s performance and costs.
We started with Traceloop because it seemed beginner-friendly, but after a month we switched to Langfuse. I wanted to share my raw, beginner-level comparison since I couldn’t find many posts from this perspective.
The main reason we switched was the dashboard. Traceloop’s felt a bit too high-level for what we needed. I wanted to drill into specific user sessions or see patterns in failed tool calls, and it felt like I had to click through too many places. Langfuse’s dashboard just made more intuitive sense to me—I could see traces, spans, and costs all in one place without feeling lost.
Setting up Langfuse took a bit more initial config (I had to wrestle with the Python SDK for an afternoon), but the documentation was really clear. With Traceloop, it was quicker to get “something” running, but we hit limits faster, especially around custom tagging and tracking user feedback. In Langfuse, I can easily tag a trace with the Asana project ID it touched, which is huge for us.
Pricing-wise, both have generous free tiers for a team our size. But Langfuse’s model (pay per trace) feels like it’ll scale better for us than Traceloop’s credit system, which was a bit confusing to estimate.
Has anyone else made a similar switch? I’m especially curious about how you handle integrating observability data back into your project management workflows. Thx!