Phase 3: The Rules of Chaos

A single server is reliable. A distributed system is a lie. Networks fail, clocks drift, and nodes die. This phase is about surviving the inevitable chaos of scale.

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CAP Theorem

Lesson 01

The physics of distributed systems. Why you can't have it all, and how to choose what to sacrifice.

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sync_problem

Consistency Models

Lesson 02

Strong, Eventual, Causal. Defining exactly when your users see the latest data.

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Replication

Lesson 03

Single Leader, Multi-Leader, Leaderless. How to keep copies of data without losing your mind.

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Partitioning (Sharding)

Lesson 04

Splitting data across servers. Horizontal scaling, hot spots, and rebalancing nightmares.

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receipt

Transactions & Sagas

Lesson 05

ACID across services? 2PC vs Sagas. How to handle partial failures in a distributed workflow.

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handshake

Consensus

Lesson 06

Paxos, Raft, and Gossip. How nodes agree on the truth in a hostile network.

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