Log Analysis

Table of Contents

• Overview
• When to Use
• Quick Start
• Reference Guides
• Best Practices

Overview

Logs are critical for debugging and monitoring. Effective log analysis quickly identifies issues and enables root cause analysis.

When to Use

• Troubleshooting errors
• Performance investigation
• Security incident analysis
• Auditing user actions
• Monitoring application health

Quick Start

Minimal working example:

// Good: Structured logs (machine-readable)
logger.info({
  level: 'INFO',
  timestamp: '2024-01-15T10:30:00Z',
  service: 'auth-service',
  user_id: '12345',
  action: 'user_login',
  status: 'success',
  duration_ms: 150,
  ip_address: '192.168.1.1'
});

// Bad: Unstructured logs (hard to parse)
console.log('User 12345 logged in successfully in 150ms from 192.168.1.1');

// JSON Format (Elasticsearch friendly)
{
  "@timestamp": "2024-01-15T10:30:00Z",
  "level": "ERROR",
  "service": "api-gateway",
  "trace_id": "abc123",
  "message": "Database connection failed",
  "error": {
    "type": "ConnectionError",
    "code": "ECONNREFUSED"
// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

| Guide | Contents | |---|---| | Structured Logging | Structured Logging | | Log Levels & Patterns | Log Levels & Patterns | | Log Analysis Tools | Log Analysis Tools | | Common Log Analysis Queries | Common Log Analysis Queries |

Best Practices

✅ DO

• Follow established patterns and conventions
• Write clean, maintainable code
• Add appropriate documentation
• Test thoroughly before deploying

❌ DON'T

• Skip testing or validation
• Ignore error handling
• Hard-code configuration values