langfuse-deploy-integration

Langfuse Deploy Integration

Overview

Deploy Langfuse observability with your application across various platforms.

Prerequisites

• Langfuse production API keys
• Deployment platform access (Vercel, AWS, GCP, etc.)
• Application ready for deployment

Instructions

Step 1: Vercel Deployment

# Set environment variables
vercel env add LANGFUSE_PUBLIC_KEY production
vercel env add LANGFUSE_SECRET_KEY production
vercel env add LANGFUSE_HOST production

// vercel.json
{
  "env": {
    "LANGFUSE_HOST": "https://cloud.langfuse.com"
  }
}

// Next.js API route with Langfuse
// app/api/chat/route.ts
import { Langfuse } from "langfuse";
import { NextResponse } from "next/server";

// Initialize outside handler for connection reuse
const langfuse = new Langfuse({
  publicKey: process.env.LANGFUSE_PUBLIC_KEY!,
  secretKey: process.env.LANGFUSE_SECRET_KEY!,
  flushAt: 1, // Flush immediately in serverless
});

export async function POST(request: Request) {
  const { message } = await request.json();

  const trace = langfuse.trace({
    name: "api/chat",
    input: { message },
    metadata: {
      platform: "vercel",
      region: process.env.VERCEL_REGION,
    },
  });

  try {
    const response = await processChat(message, trace);

    trace.update({ output: response });

    // Flush before response in serverless
    await langfuse.flushAsync();

    return NextResponse.json(response);
  } catch (error) {
    trace.update({ level: "ERROR", statusMessage: String(error) });
    await langfuse.flushAsync();
    throw error;
  }
}

Step 2: AWS Lambda Deployment

// handler.ts
import { Langfuse } from "langfuse";
import { APIGatewayEvent, Context } from "aws-lambda";

// Initialize outside handler for warm start reuse
const langfuse = new Langfuse({
  publicKey: process.env.LANGFUSE_PUBLIC_KEY!,
  secretKey: process.env.LANGFUSE_SECRET_KEY!,
  flushAt: 1, // Immediate flush for Lambda
});

export async function handler(event: APIGatewayEvent, context: Context) {
  // Don't wait for event loop to empty
  context.callbackWaitsForEmptyEventLoop = false;

  const trace = langfuse.trace({
    name: "lambda/handler",
    input: JSON.parse(event.body || "{}"),
    metadata: {
      requestId: context.awsRequestId,
      functionName: context.functionName,
      coldStart: !global.isWarm,
    },
  });

  global.isWarm = true;

  try {
    const result = await processRequest(event, trace);

    trace.update({ output: result });

    // CRITICAL: Flush before Lambda freezes
    await langfuse.flushAsync();

    return {
      statusCode: 200,
      body: JSON.stringify(result),
    };
  } catch (error) {
    trace.update({ level: "ERROR", statusMessage: String(error) });
    await langfuse.flushAsync();

    return {
      statusCode: 500,
      body: JSON.stringify({ error: "Internal error" }),
    };
  }
}

# serverless.yml
service: my-llm-app

provider:
  name: aws
  runtime: nodejs20.x
  environment:
    LANGFUSE_PUBLIC_KEY: ${ssm:/langfuse/public-key}
    LANGFUSE_SECRET_KEY: ${ssm:/langfuse/secret-key}
    LANGFUSE_HOST: https://cloud.langfuse.com

functions:
  chat:
    handler: handler.handler
    timeout: 30
    events:
      - http:
          path: /chat
          method: post

Step 3: Google Cloud Run Deployment

# Dockerfile
FROM node:20-slim

WORKDIR /app

COPY package*.json ./
RUN npm ci --production

COPY . .
RUN npm run build

# Cloud Run sets PORT
ENV PORT=8080

CMD ["node", "dist/server.js"]

// server.ts
import express from "express";
import { Langfuse } from "langfuse";

const app = express();
const langfuse = new Langfuse({
  publicKey: process.env.LANGFUSE_PUBLIC_KEY!,
  secretKey: process.env.LANGFUSE_SECRET_KEY!,
});

// Graceful shutdown for Cloud Run
process.on("SIGTERM", async () => {
  console.log("SIGTERM received, flushing Langfuse...");
  await langfuse.shutdownAsync();
  process.exit(0);
});

app.post("/chat", async (req, res) => {
  const trace = langfuse.trace({
    name: "cloudrun/chat",
    input: req.body,
    metadata: {
      service: process.env.K_SERVICE,
      revision: process.env.K_REVISION,
    },
  });

  // ... handler logic
});

const port = process.env.PORT || 8080;
app.listen(port, () => {
  console.log(`Server listening on port ${port}`);
});

# Deploy to Cloud Run
gcloud run deploy my-llm-app \
  --source . \
  --region us-central1 \
  --set-env-vars "LANGFUSE_PUBLIC_KEY=$LANGFUSE_PUBLIC_KEY" \
  --set-secrets "LANGFUSE_SECRET_KEY=langfuse-secret-key:latest" \
  --allow-unauthenticated

Step 4: Docker Compose Deployment

# docker-compose.yml
version: '3.8'

services:
  app:
    build: .
    ports:
      - "3000:3000"
    environment:
      - NODE_ENV=production
      - LANGFUSE_PUBLIC_KEY=${LANGFUSE_PUBLIC_KEY}
      - LANGFUSE_SECRET_KEY=${LANGFUSE_SECRET_KEY}
      - LANGFUSE_HOST=https://cloud.langfuse.com
    healthcheck:
      test: ["CMD", "curl", "-f", "http://localhost:3000/health"]
      interval: 30s
      timeout: 10s
      retries: 3
    deploy:
      resources:
        limits:
          memory: 512M
    restart: unless-stopped

  # Optional: Local Langfuse for development
  langfuse:
    image: langfuse/langfuse:latest
    ports:
      - "3001:3000"
    environment:
      - DATABASE_URL=postgresql://postgres:postgres@db:5432/langfuse
      - NEXTAUTH_SECRET=${NEXTAUTH_SECRET}
      - NEXTAUTH_URL=http://localhost:3001
      - SALT=${LANGFUSE_SALT}
    depends_on:
      - db
    profiles:
      - local

  db:
    image: postgres:15-alpine
    environment:
      - POSTGRES_USER=postgres
      - POSTGRES_PASSWORD=postgres
      - POSTGRES_DB=langfuse
    volumes:
      - langfuse-db:/var/lib/postgresql/data
    profiles:
      - local

volumes:
  langfuse-db:

Step 5: Kubernetes Deployment

# k8s/deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: llm-app
spec:
  replicas: 3
  selector:
    matchLabels:
      app: llm-app
  template:
    metadata:
      labels:
        app: llm-app
    spec:
      containers:
        - name: app
          image: myregistry/llm-app:latest
          ports:
            - containerPort: 3000
          env:
            - name: LANGFUSE_PUBLIC_KEY
              valueFrom:
                secretKeyRef:
                  name: langfuse-secrets
                  key: public-key
            - name: LANGFUSE_SECRET_KEY
              valueFrom:
                secretKeyRef:
                  name: langfuse-secrets
                  key: secret-key
            - name: LANGFUSE_HOST
              value: "https://cloud.langfuse.com"
          resources:
            requests:
              memory: "256Mi"
              cpu: "250m"
            limits:
              memory: "512Mi"
              cpu: "500m"
          livenessProbe:
            httpGet:
              path: /health
              port: 3000
            initialDelaySeconds: 10
            periodSeconds: 30
          lifecycle:
            preStop:
              exec:
                command: ["/bin/sh", "-c", "sleep 10"]
      terminationGracePeriodSeconds: 30
---
apiVersion: v1
kind: Secret
metadata:
  name: langfuse-secrets
type: Opaque
stringData:
  public-key: pk-lf-...
  secret-key: sk-lf-...

Output

• Platform-specific deployment configurations
• Serverless optimizations (immediate flush)
• Graceful shutdown handling
• Secret management integration
• Health checks configured

Serverless Considerations

Error Handling

Resources

• Vercel Environment Variables
• AWS Lambda Best Practices
• Cloud Run Secrets
• Langfuse Self-Hosting

Next Steps

For webhooks and events, see langfuse-webhooks-events.