Langfuse prod checklist
'Langfuse production readiness checklist and verification.From its SKILL.md
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SKILL.md
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Langfuse Production Checklist
Overview
Comprehensive checklist for deploying Langfuse observability to production with verified configuration, error handling, graceful shutdown, monitoring, and a pre-deployment verification script.
Prerequisites
- Development and staging testing completed
- Production Langfuse project created with separate API keys
- Secret management solution in place
Production Configuration
Recommended SDK Settings
// v4+ Production Config
import { LangfuseSpanProcessor } from "@langfuse/otel";
import { NodeSDK } from "@opentelemetry/sdk-node";
const processor = new LangfuseSpanProcessor({
exportIntervalMillis: 5000, // Flush every 5s
maxExportBatchSize: 50, // Batch size
maxQueueSize: 2048, // Buffer limit
});
const sdk = new NodeSDK({ spanProcessors: [processor] });
sdk.start();
// Graceful shutdown on all signals
for (const signal of ["SIGTERM", "SIGINT", "SIGUSR2"]) {
process.on(signal, async () => {
await sdk.shutdown();
process.exit(0);
});
}
// v3 Legacy Production Config
import { Langfuse } from "langfuse";
const langfuse = new Langfuse({
flushAt: 25, // Balance between latency and efficiency
flushInterval: 5000, // 5 second flush interval
requestTimeout: 15000, // 15s timeout
enabled: true, // Explicitly enable
});
process.on("beforeExit", () => langfuse.shutdownAsync());
process.on("SIGTERM", () => langfuse.shutdownAsync().then(() => process.exit(0)));
Production Error Handling
import { observe, updateActiveObservation, startActiveObservation } from "@langfuse/tracing";
// Wrap all traced operations with error safety
const tracedEndpoint = observe({ name: "api-endpoint" }, async (req: Request) => {
try {
updateActiveObservation({
input: { path: req.url, method: req.method },
metadata: { userId: req.userId },
});
const result = await processRequest(req);
updateActiveObservation({ output: { status: 200 } });
return result;
} catch (error) {
// Log error to trace -- don't let tracing error mask app error
try {
updateActiveObservation({
output: { error: String(error) },
metadata: { level: "ERROR" },
});
} catch {
// Tracing failure must never break the app
}
throw error;
}
});
Pre-Deployment Verification Script
// scripts/verify-langfuse-prod.ts
import { LangfuseClient } from "@langfuse/client";
import { startActiveObservation, updateActiveObservation } from "@langfuse/tracing";
async function verify() {
const checks: Array<{ name: string; pass: boolean; detail: string }> = [];
// 1. Environment variables
const requiredVars = ["LANGFUSE_PUBLIC_KEY", "LANGFUSE_SECRET_KEY"];
for (const v of requiredVars) {
checks.push({
name: `Env: ${v}`,
pass: !!process.env[v],
detail: process.env[v] ? `SET (${process.env[v]!.slice(0, 10)}...)` : "MISSING",
});
}
// 2. Key validation
const pk = process.env.LANGFUSE_PUBLIC_KEY || "";
const sk = process.env.LANGFUSE_SECRET_KEY || "";
checks.push({
name: "Key format",
pass: pk.startsWith("pk-lf-") && sk.startsWith("sk-lf-"),
detail: `Public: ${pk.startsWith("pk-lf-")}, Secret: ${sk.startsWith("sk-lf-")}`,
});
// 3. API connectivity
try {
const langfuse = new LangfuseClient();
// Try fetching prompts as a connectivity test
await langfuse.prompt.get("__health-check__").catch(() => {});
checks.push({ name: "API connectivity", pass: true, detail: "Connected" });
} catch (error) {
checks.push({ name: "API connectivity", pass: false, detail: String(error) });
}
// 4. Trace creation
try {
await startActiveObservation("prod-verify", async () => {
updateActiveObservation({
input: { test: true },
output: { verified: true },
metadata: { verification: "pre-deploy" },
});
});
checks.push({ name: "Trace creation", pass: true, detail: "Trace created" });
} catch (error) {
checks.push({ name: "Trace creation", pass: false, detail: String(error) });
}
// Report
console.log("\n=== Langfuse Production Verification ===\n");
let allPassed = true;
for (const check of checks) {
const icon = check.pass ? "PASS" : "FAIL";
console.log(` [${icon}] ${check.name}: ${check.detail}`);
if (!check.pass) allPassed = false;
}
console.log(`\n${allPassed ? "All checks passed." : "SOME CHECKS FAILED."}\n`);
if (!allPassed) process.exit(1);
}
verify();
Production Checklist
Authentication & Security
- Production API keys created (separate from dev/staging)
- Keys stored in secret manager (not env files or code)
- Key prefix validated at startup (
pk-lf-/sk-lf-) - PII scrubbing enabled on trace inputs/outputs
- Secret scanning in CI/CD pipeline
SDK Configuration
- Singleton client pattern (no per-request instantiation)
- Batch size tuned (
flushAt: 25-50) - Flush interval set (
flushInterval: 5000) - Request timeout configured (
requestTimeout: 15000)
Reliability
- Graceful shutdown on SIGTERM/SIGINT
- All spans end in
try/finally(v3) or useobserve/startActiveObservation(v4+) - Tracing errors caught -- never crash the app
- Circuit breaker for sustained failures
Monitoring
- Trace creation success/failure logged
- Flush latency tracked
- Rate limit errors monitored
- Dashboard alerts for quality score regression
Operations
- Runbook documented for Langfuse outages
- Fallback behavior defined (app works without Langfuse)
- Data retention policy configured
- Log rotation includes redaction of API keys
Error Handling
| Issue | Cause | Solution |
|---|---|---|
| Missing traces in prod | No flush on exit | Add shutdown handler for SIGTERM |
| Memory growth | Client created per request | Use singleton pattern |
| High latency | Small batches | Increase flushAt to 25-50 |
| Lost traces on deploy | No graceful shutdown | Add SIGTERM handler with sdk.shutdown() |
Resources
What ships with it: 1 file
5.3 KB alongside SKILL.md
references/
- implementation.md5.3 KB