Analyze application and system logs to identify errors, patterns, and root causes. Use log aggregation tools and structured logging for effective debugging.
Install
npx skills add https://github.com/aj-geddes/useful-ai-prompts --skill log-analysisSKILL.md
Log Analysis
Table of Contents
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
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