System Design Course

System Design Course

Share this post

System Design Course
System Design Course
Day 22: Building Your First Multi-Node Storage Cluster - When One Machine Just Isn't Enough
Copy link
Facebook
Email
Notes
More

Day 22: Building Your First Multi-Node Storage Cluster - When One Machine Just Isn't Enough

From the 254-Day Hands-On System Design Series

System Design Course's avatar
System Design Course
Jun 02, 2025
∙ Paid
3

Share this post

System Design Course
System Design Course
Day 22: Building Your First Multi-Node Storage Cluster - When One Machine Just Isn't Enough
Copy link
Facebook
Email
Notes
More
3
Share
  • The Pizza Delivery Problem That Explains Everything

  • Why Single Points of Failure Are System Killers

  • The Architecture: Simple but Powerful

  • Understanding the Data Flow

  • The Implementation Strategy

  • Real-World Challenges and Solutions

  • Integration with Your Log Processing System

  • Production Insights from the Trenches

  • What You'll Build Today

  • Multi-Node Storage Cluster Implementation Guide

  • Troubleshooting Common Issues

  • Build, Test, and Verify Guide

  • Multi-Node Storage Cluster with File Replication

  • Troubleshooting Guide

The Pizza Delivery Problem That Explains Everything

Imagine you're running a pizza delivery service with just one restaurant. Everything works great until Friday night hits—orders flood in, your single kitchen gets overwhelmed, and customers start canceling. Sound familiar? This is exactly what happens when your log processing system relies on a single storage node.

Yesterday, we built a log enrichment pipeline that adds valuable context to our raw logs. But here's the reality check: all that enriched data hitting one storage node creates a bottleneck that'll crush your system faster than a pizza oven on New Year's Eve.

Today, we're solving this by building a multi-node storage cluster with file replication—essentially opening multiple pizza kitchens that can cover for each other when one goes down.

Why Single Points of Failure Are System Killers

In production systems handling millions of log entries per second (think Netflix, Uber, or AWS), a single storage node is like having one person handle all customer support tickets. It's not just about capacity—it's about resilience. When that node fails (and it will), you lose everything.

Multi-node clusters solve three critical problems:

  • Availability: Other nodes keep serving when one fails

  • Scalability: Distribute load across multiple machines

  • Durability: Replicated data survives hardware failures

Real-world example: When GitHub experienced a major outage in 2018, their multi-node storage cluster meant they could restore service quickly instead of losing millions of repositories forever.

The Architecture: Simple but Powerful

Our multi-node cluster consists of three key components:

Storage Nodes: Individual machines that store log files locally. Each node maintains its own file system but coordinates with others.

Replication Manager: Coordinates copying files between nodes. Think of it as the dispatcher ensuring every pizza recipe exists in multiple kitchens.

Health Monitor: Continuously checks node availability and triggers failover when needed.

The magic happens in the replication strategy. We'll implement asynchronous replication—when a log file is written to the primary node, it's simultaneously copied to secondary nodes in the background. This approach balances performance with reliability.

Understanding the Data Flow

This post is for paid subscribers

Already a paid subscriber? Sign in
© 2025 System Design Course
Privacy ∙ Terms ∙ Collection notice
Start writingGet the app
Substack is the home for great culture

Share

Copy link
Facebook
Email
Notes
More