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PandaProbe
open source agent engineering platform
887 followers
open source agent engineering platform
887 followers
PandaProbe is an open-source agent engineering platform that gives you deep observability into AI agent applications. Use it to trace, evaluate, monitor and debug your AI agents in development and production.
Tobira.ai
Congrats on launching! How does PandaProbe handle sub-agent calls? Like if agent A spins up agent B, do both get traced under the same session tree
PandaProbe
We use LangGraph for these purposes. How is PandaProbe better and why should we switch to it?
PandaProbe
We've been running Langfuse for our agent stack for about six months and the trace UI is decent, but session-level evals across multi-agent runs are still where things get messy. Curious how PandaProbe handles that. If a sub-agent fails three turns deep, do you surface root cause at the session level, or do I still have to walk the span tree manually? Also, what's the storage model look like for self-hosted? Postgres only, or something columnar for the trace volume? One more thing: any plans for OpenTelemetry-native ingestion so I don't have to swap out my existing tracing SDK across services?
Triforce Todos
Congratulations on the launch @sina_tayebati
BTW, how well does PandaProbe handle tracking regressions across different agent versions over time?
PandaProbe
Origio
Honestly the open source + self hostable combo is what makes this worth a proper look. most observability tools want you locked into their cloud and charging per seat by the time you actually need it. been burned by that before with Datadog at a startup. one instrument() call to trace the whole run is a nice dx too, gonna try this on a side project this week
PandaProbe
@shlokmestry Really appreciate that — and yeah, that exact lock-in/pricing pain is something we wanted to avoid from day one.
That’s why we made it open source + self-hostable, so teams can keep full control as they scale instead of getting boxed into per-seat or per-trace pricing later.
And glad you called out the DX — we’ve been trying to make instrumentation as lightweight as possible.
Would love to hear how it works for your side project 🙌
This looks neat and seems great especially for complex AI workflows, but just thinking about it, how'd the revenue side work?
What does the integration ecosystem look like for native orchestration frameworks like LangGraph or CrewAI?