Agent skill · software engineering · jeremylongshore
langfuse-deploy-integration
Deploy Langfuse with your application across different platforms.
Why this skill is useful
Provides specific deployment scripts and integration patterns for Langfuse across multiple platforms that the AI wouldn't reliably generate on its own.
What it needs
Requires docker, gcloud, vercel installed locally. Requires langfuse account access. About 3k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
Langfuse Deploy Integration Overview Deploy Langfuse LLM observability alongside your application. Covers integrating the SDK for serverless (Vercel/Lambda), Docker, Cloud Run, and self-hosting the Langfuse server itself. Prerequisites Langfuse API keys (cloud or self-hosted) Application using Langfuse SDK Target platform CLI installed Instructions Step 1: Vercel / Next.js Deployment Serverless note: Langfuse SDK v4+ uses OTel which handles flushing asynchronously. For v3, always call await langfuse.flushAsync() before the response returns -- serverless functions may freeze after response. Step 2: AWS Lambda / Serverless Step 3: Self-Hosted Langfuse Server (Docker) Step 4: Google Cloud Run Step 5: Health Check Endpoint Platform-Specific Considerations Platform Key Concern Solution ---------- ------------- ---------- Vercel/Edge Function timeout Flush before response; use v4+ AWS Lambda Cold starts Initialize SDK outside handler Cloud Run Concurrency Singleton client, shared OTel SDK Docker Self-hosted networking Ensure app can reach Langfuse host Kubernetes Pod lifecycle Shutdown hook on SIGTERM Error Handling Issue Cause Solution ------- ------- ---------- Traces missing in serverless Not flushed before freeze sdk.shutdown() before response Auth error after deploy Wrong env for environment Verify secrets match deployment Self-hosted 502 DB not ready Add healthcheck + dependson High latency in prod Small batch size Increase flushAt / maxExportBatchSize Output Produce a deployment receipt with the target environment, deployed revision, secret reference names (never values), health endpoint result, and one verified Langfuse trace. If tracing is degraded, report the application status separately from the telemetry status so an observability outage is not misrepresented as an application outage. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/langfuse-deploy-integration