Event Driven Distributed Systems

The chapters in this module, in reading order.

#	Chapter
00	Event-Driven and Distributed Systems — The Five-Year-Old Version
01	Events vs Commands — Facts already happened, orders may still fail
02	Queues vs Streams — One worker takes the job, or many readers follow the flow
03	Kafka Deep Dive — Partitions, offsets, groups, and the promises you actually get
04	SQS, RabbitMQ, and Google Pub/Sub — Managed queue, flexible broker, or cloud fan-out pipe
05	Retries, DLQ, and Idempotency — Fail safely without duplicate side effects
06	Event sourcing — store facts first, rebuild state later
07	Saga pattern — coordinate many local commits without one global transaction
08	CQRS — split commands and queries when one model starts hurting both
09	Consistent hashing — spread keys across nodes without moving everything
10	Consensus algorithms — how distributed systems agree without trusting timing
11	Leader election — choosing one boss without accidentally choosing two
12	Service discovery — finding moving services without hardcoding moving addresses
13	Circuit breaker and bulkhead — stopping one burning room from taking the whole building
14	Honest admission — the distributed truths that still hurt after the diagrams look neat