Day 82: Correlation Analysis Across Different Log Sources
Finding the Hidden Connections That Reveal System Behavior
“254-Day Hands-On System Design Series
Module 3: Advanced Log Processing Features | Week 12: Advanced Analytics”
What We're Building Today
Today you'll create a complete correlation analysis system that automatically discovers relationships between events across different log sources. Here's what we'll build:
High-Level Components:
Multi-source log collectors that parse web, database, API, and service logs
Real-time correlation engine detecting temporal relationships within 30-second windows
Statistical analysis algorithms calculating correlation strength and confidence
Interactive React dashboard showing live correlation patterns
REST API exposing correlation data for external integrations
Key Capabilities:
Session-based correlation linking user actions across services
Error cascade detection showing how failures spread through systems
Metric correlation identifying performance relationships
Pattern learning from historical correlation data
Real-time alerts when significant correlations are detected
The Hidden Challenge in Distributed Systems
Netflix processes logs from 1000+ microservices simultaneously. When users report buffering issues, the problem might originate in CDN logs, manifest in application logs, and impact metrics logs. Traditional monitoring shows isolated symptoms - correlation analysis reveals the complete chain reaction.
Modern systems generate events across web servers, databases, application layers, and infrastructure. Each log source tells part of the story. Correlation analysis connects these fragments into coherent narratives that enable rapid troubleshooting.
