Frequently asked questions

LangSmith and Langfuse are passive tracing tools — they record what happened so you can inspect it later. Dunetrace is active: it watches the structural pattern of every run and fires a Slack alert within 15 seconds of completion. You don't have to know something broke to open a dashboard. Think of Dunetrace as your alerting layer and Langfuse as your deep-inspection layer. They work well together — get the alert from Dunetrace, then drill into the full trace in Langfuse for root cause analysis.

Less than 500µs per agent run. Events are buffered in a background thread — your agent is never blocked waiting on Dunetrace. The SDK patches OpenAI, Anthropic, and httpx globally so there is nothing to add to each call site. If the ingest service goes down, buffered events are dropped silently and your agent keeps running unaffected.

No. Every prompt, tool argument, and model output is SHA-256 hashed inside your agent process before anything is transmitted. Dunetrace detects structural patterns — call counts, latencies, error rates, token growth — not content. Raw text never leaves your infrastructure.

Python and TypeScript/Node. In Python: first-class support for LangChain, LangGraph, CrewAI, AutoGen, and Haystack. Any other framework works via @dt.agent() decorator or context manager. FastAPI, Flask, and ASGI/WSGI apps are supported via middleware. The TypeScript SDK wraps OpenAI and Anthropic clients with dt.wrapOpenAI() / dt.wrapAnthropic(). Zero-code instrumentation is available for any OpenTelemetry-compatible pipeline (Langdock, Dify, etc.).

Yes. Edit detectors.yml in the repo root — no code changes or rebuilds needed. You can set per-agent overrides too. For example, a web-research agent that legitimately repeats queries can have a higher tool-loop threshold than your other agents. Apply changes with docker compose restart detector.

The SDK buffers up to 10,000 events locally and your agent runs unaffected. Once the service recovers, buffered events are shipped automatically. The detector worker processes all queued runs on restart — so signals and alerts are delayed, not lost.

Add SLACK_WEBHOOK_URL to your .env file, then restart the alerts worker: docker compose restart alerts. Optionally set SLACK_CHANNEL and SLACK_MIN_SEVERITY to filter noise. Get a webhook URL from api.slack.com/messaging/webhooks. Generic webhooks (PagerDuty, Linear, custom) are also supported — set WEBHOOK_URL instead.