log-aggregation

All your logs in one place. Search across services, find errors instantly, spot anomalies before they become outages — no SSH needed.

What It Does

• Collect logs — From files, stdout, syslog, Docker, cloud services
• Search — Full-text search with filters and time ranges
• Parse — Auto-detect formats, extract fields (JSON, Apache, custom)
• Aggregate — Group by service, level, time bucket
• Alert — Trigger on error rate spikes, specific patterns
• Export — To files, SIEM systems, or dashboards

Quick Start

# 1. Collect logs from your app
collect logs from /var/log/myapp/*.log

# 2. Search for errors
search error logs from last hour

# 3. Find specific pattern
search logs containing "payment failed" from today

# 4. Check error rate
get error count per minute from last 30 minutes

Common Use Cases

🐛 Debug Production Issue

# User reported error at 2:30 PM
search logs containing "user_id=12345" from 2:00 PM to 2:45 PM

# Find the stack trace
search logs containing "Exception" after "user_id=12345"

🚨 Monitor Error Spikes

# Check error rate
get error count per minute from last hour

# Set up alert
alert when error rate exceeds 10 per minute

# Alert on specific pattern
alert when logs contain "OutOfMemoryError"

📊 Analyze Performance

# Find slow requests
search logs containing "duration > 1000ms" from today

# Group by endpoint
aggregate logs by request_path calculate avg(duration)

🔍 Security Audit

# Find failed logins
search logs containing "login failed" from last 7 days

# Check for suspicious patterns
search logs containing "SELECT *" or "DROP TABLE" from last 24 hours

All Commands

Supported Log Sources

Files: /var/log/*.log, rotating logs, compressed archives

Docker: Container stdout/stderr

Cloud: AWS CloudWatch, GCP Logging, Azure Monitor

Syslog: Local and remote syslog

Applications: Node.js, Python, Java, Go loggers

Requirements

• Node.js 18+
• Optional: Elasticsearch or Loki for large-scale storage
• Optional: Grafana for visualization