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pino

Pino - extremely fast and low overhead Node.js logger with JSON-native structured logging. 10x faster than Winston. Optimized for high-performance APIs and production environments. USE WHEN: user mentions "pino", "fast logging", "high performance logging", "fastify logging", asks about "fastest node.js logger", "JSON structured logging", "low overhead logging" DO NOT USE FOR: Winston logging - use `winston` instead, Python logging - use `python-logging` instead, Complex transport requirements - use `winston` instead

personAuthor: jakexiaohubgithub

Pino Logger - Quick Reference

When to Use This Skill

  • Structured logging in Node.js applications
  • High-performance logging
  • Integration with log aggregation systems

Deep Knowledge: Use mcp__documentation__fetch_docs with technology: pino for comprehensive documentation.

Basic Setup

npm install pino pino-pretty

Essential Patterns

Logger Base

import pino from 'pino';

const logger = pino({
  level: process.env.LOG_LEVEL || 'info',
  transport: {
    target: 'pino-pretty',
    options: { colorize: true }
  }
});

logger.info('Server started');
logger.error({ err }, 'Failed to connect');

Child Logger

const childLogger = logger.child({
  module: 'auth',
  requestId: req.id
});

childLogger.info({ userId }, 'User authenticated');

Express Integration

import pinoHttp from 'pino-http';

app.use(pinoHttp({ logger }));

Fastify Integration

import Fastify from 'fastify';

const fastify = Fastify({
  logger: {
    level: 'info',
    transport: {
      target: 'pino-pretty'
    }
  }
});

Production Configuration

const logger = pino({
  level: 'info',
  formatters: {
    level: (label) => ({ level: label }),
  },
  timestamp: pino.stdTimeFunctions.isoTime,
  base: {
    pid: process.pid,
    hostname: os.hostname(),
  },
});

When NOT to Use This Skill

  • Complex multi-transport requirements: Winston offers more flexible transport system
  • Custom log formatting beyond JSON: Winston has more formatting options
  • Development-only logging: Built-in console is simpler for quick debugging
  • Python/Java projects: Use language-specific logging frameworks
  • Legacy apps expecting text logs: Pino is JSON-first, requires parsing tools

Anti-Patterns

| Anti-Pattern | Why It's Bad | Solution | |--------------|--------------|----------| | Using pino-pretty in production | 2-3x performance penalty | Only use in development, raw JSON in prod | | Logging large objects | Serialization overhead | Log only necessary fields | | Synchronous logging | Defeats Pino's async advantage | Use default async mode, avoid pino.final() | | Nested child loggers without cleanup | Memory leak over time | Reuse child loggers or clear references | | Logging in hot paths without level check | Still has minimal overhead | Use if (logger.isLevelEnabled('debug')) for extreme cases | | Mixing multiple logger instances | Inconsistent configuration | Create one base logger, use child loggers |

Quick Troubleshooting

| Issue | Cause | Solution | |-------|-------|----------| | Unreadable JSON in console | No pretty-printer configured | Add pino-pretty transport for development | | Performance slower than expected | pino-pretty enabled in production | Remove pretty-printer, use raw JSON | | Missing logs | Level too high | Check level configuration matches environment | | Context not included | Not using child logger | Use logger.child({ context }) for request scoping | | Logs not flushing on exit | Async logging buffer | Use pino.final() or flush on SIGTERM | | Extra fields not appearing | Incorrect syntax | Use object as first param: logger.info({ field }, 'msg') |