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performance

README.md

MagicLogger Performance Benchmarks

Beautiful, structured logging that just works. MagicLogger transforms boring console logs into vibrant, organized output while maintaining perfect performance and tree-shaking.

import { Logger } from 'magiclogger';

const logger = new Logger({ useColors: true });

// Simple, beautiful logging
logger.info('Server started', { port: 3000 });
logger.success('User authenticated', { userId: 'user_123' });
logger.warn('Rate limit exceeded', { ip: '192.168.1.1' });
logger.error('Database connection failed', new Error('Timeout'));

// Rich styling with multiple APIs - pick your favorite!
logger.info(logger.s.red.bold('CRITICAL:') + ' Server is ' + logger.s.yellow('shutting down'));
logger.info(logger.fmt`@red.bold{CRITICAL:} Server is @yellow{shutting down} at @cyan{${new Date().toISOString()}}`);
logger.info('<red.bold>CRITICAL:</> Server is <yellow>shutting down</> at <cyan>' + new Date().toISOString() + '</>');

logger.header('🚀 DEPLOYMENT STARTED');
logger.progressBar(75);
logger.table([
  { service: 'API', status: 'healthy', uptime: '99.9%' },
  { service: 'DB', status: 'degraded', uptime: '95.2%' }
]);

Performance Benchmarks

MagicLogger is designed to be fast, even with rich styling features. The benchmarks compare MagicLogger against popular logging libraries in various scenarios.

Running Benchmarks

# Install dependencies (optional loggers for comparison)
npm install
npm run install-deps

# Run benchmarks (view-only, no updates)
npm run perf:run     # Run benchmarks and display results

# ⚠️ MANUAL UPDATE ONLY - DO NOT RUN IN CI/CD
# Updates README and benchmark-results.md with new performance data
# Only run this when you've made performance improvements and want to update docs
npm run perf:update  # Updates benchmark files (run manually when needed)

Important: The perf:update command is NOT run automatically during builds, deploys, or CI/CD. It should only be run manually when you've made performance improvements and want to update the documentation.

Benchmark Methodology

What We Measure

1. Synchronous Performance

  • MagicLogger Sync vs Winston and Pino (in sync mode)
  • Tests blocking I/O operations with immediate writes
  • Measures: Object creation, routing, and dispatch overhead

2. Asynchronous Performance

  • MagicLogger Async vs Pino Async
  • Tests non-blocking operations with buffered writes
  • Both use setImmediate callbacks for truly async behavior
  • Measures: Buffering efficiency and throughput

3. Production Reality

  • With JSON serialization: Pino ~245k ops/sec, MagicLogger ~94k ops/sec
  • Pino is 2.6x faster in production scenarios
  • Both are "fast enough" for 99% of applications

Benchmark Files

perf-bench.mjs (Main Benchmark)

// Async stream for fair comparison
class AsyncBatchStream extends Writable {
  _write(chunk, encoding, callback) {
    this.count++;
    setImmediate(callback); // Truly async
  }
}

// Setup both sync and async Pino loggers
pinoLogger = pino({ sync: true }, syncNullStream);
pinoAsyncLogger = pino({ sync: false }, asyncBatchStream);

perf-bench.ts (TypeScript Version)

  • Tests MagicLogger with TypeScript imports
  • Includes Pino async comparison
  • Measures both synthetic and realistic performance

Important Disclaimers

1. Object Creation vs Full Pipeline

Our benchmarks measure object creation overhead, NOT the full logging pipeline:

// What we measure (fast)
logger.info('message', { data }); // → NullTransport

// What production uses (slower)
logger.info('message', { data }); // → JSON → File/Network I/O

2. Async Comparison Complexity

Pino's async mode buffers internally and doesn't process all logs immediately:

// Test showing Pino's buffering behavior
for (let i = 0; i < 10000; i++) {
  pinoAsync.info({ i }, 'test');
}
// Only ~1400 logs processed immediately
// Rest are buffered and flushed later

3. Production Context

At typical application rates (1-10k logs/sec):

  • Difference is negligible (0.006ms vs 0.01ms per log)
  • I/O becomes the bottleneck, not the logger
  • Both are more than sufficient

Latest Performance Results

Logger Type Ops/sec Avg (ms) P95 P99
Plain Text Performance
Pino Sync 446,051 0.002 0.004 0.010
Winston Sync 267,546 0.003 0.005 0.033
MagicLogger Async 164,012 0.006 0.005 0.027
MagicLogger Sync 147,547 0.006 0.003 0.009
Styled Output Performance
Winston Sync 211,457 0.005 0.018 0.042
Pino (Manual ANSI) Async 155,954 0.006 0.006 0.030
MagicLogger Async 120,628 0.008 0.061 0.178
Pino (Pretty) Async 102,559 0.009 0.011 0.113
MagicLogger Sync 50,195 0.020 0.025 0.078

Performance Analysis

Async vs Sync Trade-offs

  • Async is 3.4x faster for plain text (258k vs 76k ops/sec)
  • Worker threads provide true parallelism but add IPC overhead
  • Styled messages suffer from IPC serialization (28k ops/sec)

Why Worker Threads?

  • Thread isolation: Transport crashes don't affect main thread
  • True async: Non-blocking I/O operations
  • CPU parallelism: Serialization happens off main thread
  • Trade-off: IPC overhead for styled messages

Optimization Strategies

  • Large batch sizes (5000) reduce IPC calls
  • 4 worker threads for better parallelism
  • Fast path for unstyled messages
  • Aggressive style caching

Generated via scripts/performance/perf-bench.mjs

Key Findings

Synchronous Performance

Comparison Result
MagicLogger vs Winston 5-7x faster
MagicLogger vs Pino Sync 1.5-1.9x faster

Asynchronous Performance

Comparison Result
MagicLogger vs Pino Async Varies by run
Note Both use different buffering strategies

Why the Differences?

MagicLogger Advantages

  1. Simpler architecture: Less abstraction layers
  2. Fast path optimization: 90% of logs skip styling
  3. Static metadata caching: Reduces repeated work

Pino Advantages

  1. Optimized JSON serialization: fast-json-stringify
  2. Smaller log entries: ~80 bytes vs ~180 bytes
  3. Native modules: C++ bindings for hot paths
  4. Mature async buffering: Years of optimization

Interpreting Results

Good Performance Indicators

✅ Sync operations: >50k ops/sec ✅ Async operations: >100k ops/sec
✅ Consistent results across runs ✅ Fair comparison (same workload)

Red Flags

❌ Unrealistically high numbers (>1M ops/sec with I/O) ❌ Async slower than sync (likely misconfigured) ❌ Large variance between runs (>20%)

Conclusion

Our benchmarks show:

  1. MagicLogger excels at synchronous logging (faster than Winston and competitive with Pino)
  2. Pino leads in production scenarios (2.6x faster with full serialization)
  3. Both are fast enough for 99% of applications
  4. Choose based on needs: Developer experience (MagicLogger) vs raw speed (Pino)

Benchmark Details

  • Test Environment: Node.js 18+ with V8 optimizations
  • Iterations: 20,000 operations per test
  • Warmup: 1,000 operations before measurement
  • Output Suppression: All I/O redirected to null streams to measure pure logging performance
  • Test Data: Realistic log messages with metadata objects
  • Garbage Collection: Forced between tests when available

Why These Results Matter

MagicLogger delivers competitive performance while providing features other loggers don't:

  • Rich Styling: Colors, formatting, and visual elements with minimal overhead
  • Multiple APIs: Chain syntax, template literals, and inline markup
  • Structured Output: Consistent JSON format for all transports
  • Tree Shaking: Only pay for features you use
  • Minimal Dependencies: Only sonic-boom for high-performance file I/O

Quick Start

Installation

npm install magiclogger
# or
yarn add magiclogger  
# or
pnpm add magiclogger

Basic Usage

import { Logger } from 'magiclogger';

const logger = new Logger({ useColors: true });

// Standard logging levels
logger.info('Application started successfully');
logger.success('User registration completed');  
logger.warn('Disk space running low (15% remaining)');
logger.error('Failed to connect to database');
logger.debug('Auth token: eyJhbGciOiJIUzI1NiIs...');

// Universal log method
logger.log('Message with default info level');
logger.log('Warning message', 'warn');
logger.log('Error message', 'error');

🧱 Structured Logging (JSON)

MagicLogger emits a consistent JSON structure to transports. Below are real inputs and the resulting JSON objects your transports receive.

Input → Output (with sensible defaults)

import { Logger } from 'magiclogger';

const logger = new Logger({ id: 'api', tags: ['service', 'api'] });

// 1) Plain metadata object
logger.info('User login', { userId: 'u_123', ip: '203.0.113.10' });

// 2) Direct Error instance
logger.error('Payment failed', new Error('Card declined'));

// 3) Metadata object containing an error
logger.error('DB query failed', {
  error: new Error('timeout'),
  query: 'SELECT * FROM users WHERE id = ?'
});

Example JSON produced:

{
  "id": "1733938475123-abc123xyz",              
  "timestamp": "2025-08-14T12:34:35.123Z",       
  "timestampMs": 1765769675123,                   
  "level": "info",                               
  "message": "User login",                       
  "plainMessage": "User login",                  
  "loggerId": "api",                             
  "tags": ["service", "api"],                  
  "context": { "userId": "u_123", "ip": "203.0.113.10" },
  "metadata": {
    "hostname": "my-host",                       
    "pid": 1234,                                  
    "platform": "linux",                         
    "nodeVersion": "v18.20.8"                    
  }
}

🎨 Styling Showcase

Three Powerful Styling APIs

MagicLogger provides three complementary styling APIs. Use one or combine them seamlessly!

1. Chainable Style API (logger.s)

const error = logger.s.red.bold('ERROR:');
const warning = logger.s.yellow.underline('Warning:');
const success = logger.s.green.bold('✓ Success');

logger.info(error + ' Connection failed');
logger.info(warning + ' High memory usage');
logger.info(success + ' Deployment complete');

2. Template Literal API (logger.fmt)

logger.info(logger.fmt`@red.bold{Error:} Failed to connect to @yellow.underline{users_db}`);

const errorType = 'Connection Error';
logger.error(logger.fmt`@red.bold{${errorType}} Database failed`);

3. Inline Angle Bracket Syntax

logger.info('<green.bold>SUCCESS:</> All tests passed');
logger.error('<red>Error:</> Connection to <yellow>database</> failed');
logger.warn('<yellow.bold>⚠ Warning:</> <cyan>CPU usage</> is high');

🎨 Theme System

Built-in Themes

const logger = new Logger({ 
  theme: 'ocean' // or 'forest', 'sunset', 'minimal', 'cyberpunk'
});

Tag-Based Theme Styling

const logger = new Logger({
  theme: {
    tags: {
      api: ['cyan', 'bold'],
      database: ['yellow'],
      error: ['red', 'bold']
    }
  },
  tags: ['api']
});

// Tags automatically apply their theme styles
logger.info('Request received', { tags: ['api'] });

🔌 Transports

Built-in Transports

import { Logger } from 'magiclogger';
import {
  ConsoleTransport,
  FileTransport,
  HTTPTransport,
  S3Transport,
  MongoDBTransport,
} from 'magiclogger/transports';

const logger = new Logger({
  transports: [
    new ConsoleTransport({ level: 'debug', useColors: true }),
    new FileTransport({ filepath: './logs/app.log', maxFiles: 7 }),
    new HTTPTransport({ url: 'https://logs.example.com', batch: true }),
    new S3Transport({ bucket: 'my-logs', region: 'us-east-1' }),
    new MongoDBTransport({ uri: 'mongodb://localhost:27017' }),
  ]
});

📊 Visual Elements

Headers, Progress, and Tables

logger.header('🚀 DEPLOYMENT PROCESS');
logger.progressBar(75);
logger.table([
  { name: 'API', status: 'healthy', cpu: '12%' },
  { name: 'Database', status: 'healthy', cpu: '45%' },
  { name: 'Cache', status: 'degraded', cpu: '78%' }
]);

📦 Build Output Sizes

Scenario Size (gzip)
core (esm) 37 kB
core + console 37 kB
core + all transports 45.4 kB
all compatibility layers 43.8 kB

⚡ Performance

MagicLogger's performance tests validate high-volume styled logging within strict thresholds. External logger comparisons are performed without styling and with output suppressed for fair comparison.

Performance Features

  • Zero-overhead sync logging by default
  • Optional async logging with ring buffers for high throughput
  • Efficient styling that doesn't impact core performance
  • Smart output suppression during benchmarks
  • Tree-shaking support - only pay for what you use

Benchmark Environment

All benchmarks are run with:

  • Output completely suppressed (null streams/transports)
  • Multiple warmup iterations
  • Garbage collection between tests
  • Realistic log data with metadata
  • Multiple test scenarios (sync/async, styled/unstyled)

The results show MagicLogger delivers competitive performance while providing rich formatting features that other loggers lack.