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Day 66: Intelligent Log Redaction for Compliance

Day 66: Intelligent Log Redaction for Compliance

Module 3: Advanced Log Processing Features | Week 10: Security and Compliance

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System Design Course
Jul 16, 2025
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Day 66: Intelligent Log Redaction for Compliance
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Building Privacy-First Log Processing Systems


What We're Building Today

Core System Components:

  • Pattern Detection Engine - ML-powered sensitive data identification using regex and NLP

  • Redaction Processor - Real-time data masking with multiple strategies (mask, partial, token, hash)

  • Configuration Manager - Rule-based redaction policies for GDPR, HIPAA, PCI DSS compliance

  • Performance Monitor - Sub-millisecond redaction tracking and throughput metrics

  • Live Dashboard - Real-time redaction statistics and interactive demo interface

Integration Context: Building on Day 65's encryption system, we add proactive redaction that prevents sensitive data from entering logs. This creates defense-in-depth: redaction for prevention, encryption for protection, and tomorrow's audit trails for accountability.


The Real-World Challenge

You're running a healthcare platform processing patient data. Every user interaction, API call, and database query generates logs containing sensitive information—Social Security numbers, credit card details, medical records. Without proper redaction, you're sitting on a compliance time bomb that could trigger million-dollar GDPR fines or HIPAA violations.

Today we implement intelligent log redaction—a system that automatically identifies and masks sensitive data in real-time, ensuring compliance while preserving log utility for debugging and analytics.


Why This Matters More Than You Think

Stripe processes billions in payments and must redact credit card data from logs while preserving transaction flow visibility. Uber redacts driver locations from operational logs while maintaining route optimization capabilities. Netflix masks viewer preferences from debugging logs while preserving recommendation system insights.

The challenge isn't just finding sensitive data—it's doing it fast enough for real-time systems while maintaining log utility for operations teams.


Core Concepts: Pattern Recognition at Scale

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