Day 83: Building a Root Cause Analysis Engine - Tracing Issues to Their Origin What We’re Building Today

Mission: Create an intelligent detective system that automatically connects the dots between seemingly unrelated log events to pinpoint exactly what went wrong and when.

Key Components We’ll Implement:

• Causal relationship detector between log events

• Timeline reconstruction engine for incident analysis

• Root cause ranking system with confidence scores

• Interactive investigation dashboard for exploring failure chains

• Automated incident report generator

Expected Outcome: A production-ready system processing 10,000+ events per second with 85%+ accuracy in identifying root causes within 30 seconds.

The Real-World Problem

When Netflix experiences a streaming outage affecting millions of users, engineers don’t manually sift through terabytes of logs. They use sophisticated root cause analysis systems that trace the failure backwards through interconnected services, identifying the single API change or database timeout that triggered the cascade.

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[Component Architecture Diagram]

Your root cause analysis engine transforms chaotic log streams into clear causal narratives, automatically identifying:

• Primary triggers: The initial events that started failure cascades

• Propagation paths: How problems spread through system components

• Contributing factors: Secondary issues that amplified the impact

• Recovery points: Where interventions could have prevented escalation

Core Architecture Components

1. Event Timeline Reconstructor

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