Distributed Systems Fundamentals
Overview
This section covers the foundational concepts and theoretical results that underpin all distributed systems. Understanding these fundamentals—CAP theorem, FLP impossibility, consistency models, and time/ordering—is essential for reasoning about distributed algorithms and system design.
Topics
| Topic | Description |
|---|---|
| CAP Theorem | The fundamental trade-off between consistency, availability, and partition tolerance |
| FLP Impossibility | Why deterministic consensus is impossible in asynchronous systems with one faulty process |
| Consistency Models | The spectrum from strong to eventual consistency |
| Time and Ordering | How to order events without a global clock |
| Lamport Clocks | Logical clocks that capture happened-before relationships |
| Vector Clocks | Capturing causal dependencies across all nodes |
Key Insight
Distributed systems are fundamentally harder than single-machine systems because:
- No global state — Each node has its own view of the world
- No global clock — Nodes can’t perfectly synchronize time
- Partial failures — Some nodes may fail while others continue
- Unreliable networks — Messages can be lost, delayed, duplicated, or reordered
These constraints mean that many problems solvable on a single machine (like consensus) become provably impossible or extremely difficult in distributed settings.