Streaming — Software Architecture

Building Event-Driven Microservices source

*Building Event-Driven Microservices* — Adam Bellemare

Designing Data-Intensive Applications source

*Designing Data-Intensive Applications* — Martin Kleppmann

CDC, event sourcing, CQRS, immutability, write/read path, correctness without coordination; DDD: CQRS sync/async projections, architectural slices, event-sourced domain model four-step cycle; Fowler's four-way event taxonomy (notification/state-transfer/event-sourcing/CQRS)

Event-Driven Architecture style

Broker vs mediator topologies; DDD: three event types (notification, ECST, domain event); private vs public events; distributed big ball of mud anti-pattern; data liberation

Martin Kleppmann author

Author of *Designing Data-Intensive Applications*; distributed systems researcher at Cambridge; CRDT and local-first software advocate

Stream Processing stream

Log-based brokers (Kafka), stateless topology primitives, partition assignment, windowing, late event strategies, watermarks vs stream time, reprocessing, state stores (internal/external, changelog, hot replicas), effectively once processing, heavyweight vs lightweight framework comparison, stream joins, exactly-once fault tolerance; Kafka production mechanics: producer batching (acks/idempotence), consumer commit semantics, semantic partitioning, consumer groups, ISR