Distributed Systems Overview

What is a Distributed System

Distributed systems study how multiple computers work together to accomplish tasks that a single computer cannot. Virtually every large-scale internet service — search engines, social networks, e-commerce, cloud storage — is powered by distributed systems.

Why Learn Distributed Systems

Required for large-scale systems. Modern AI training requires thousands of GPUs working in coordination; AI inference needs deployment across global data centers.

Understand modern software architecture. Microservices, Kubernetes, message queues, distributed databases — all built on distributed systems theory.

Advanced interview topic. System Design Interviews are fundamentally about distributed system design.

Core Knowledge Modules

Fundamentals

• Definition: resource sharing, concurrency, no global clock, independent failures
• Architecture: client-server, P2P, microservices

Time and Clocks

• Clock synchronization, logical clocks (Lamport, vector clocks)

Replication and Consistency

• Replication strategies, consistency models, CAP theorem, BASE theory

Consensus Algorithms

• Paxos, Raft, ZAB, Two-Phase Commit

Distributed Data Storage

• Sharding, distributed databases, distributed file systems

Distributed Computing

• MapReduce, Spark, distributed training

How to Learn

Read classic papers first. Start with Google's "big three" (GFS, MapReduce, Bigtable).

Do the MIT 6.824 labs. Implement Raft and a Raft-based KV store.

Build a distributed cluster with Docker Compose. Deploy a Redis Cluster or Kafka cluster.

Resources in This Module