Day 53: Building Planet-Scale Search - Distributed Indexing Across Multiple Nodes
Week 8: Distributed Log Search | Module 2: Scalable Log ProcessingPart of the "254-Day Hands-On System Design" Series
🎯 What You'll Master Today
Today marks a pivotal moment in your distributed systems journey. You're transitioning from single-machine constraints to planet-scale architecture patterns used by companies processing billions of searches daily.
Learning Agenda:
Consistent Hash Ring Distribution - The mathematical foundation powering Google's distributed infrastructure
Multi-Node Query Coordination - How Netflix routes searches across thousands of machines
Fault-Tolerant Index Architecture - Building systems that survive individual node failures
Production-Scale Implementation - Complete working system handling 10,000+ documents
Performance Optimization - Achieving sub-100ms query response times across distributed nodes
By lesson's end, you'll have built the same distributed indexing patterns that power Elasticsearch's billion-document clusters and Amazon CloudSearch's managed infrastructure.
From Single Machine to Global Scale
Yesterday you built an inverted index that could search millions of log entries on a single machine. Today we're breaking that ceiling by distributing your index across multiple nodes - the same technique powering Google's search across billions of web pages.
When Elasticsearch processes 50 billion documents daily across thousands of nodes, or when Splunk indexes terabytes of enterprise logs, they're using the distributed indexing patterns you'll master today.