Go, Flink, and Spark represent different stages of real-time processing. Go handles ingestion and validation at millisecond latency, Flink maintains continuous event-time computation with state and recovery, and Spark performs large-scale analytical aggregation or feature building over recent and historical data. The choice depends on latency targets, consistency requirements, and the scope of computation.

End-to-end breakdown of high-load API systems in Go — from architectural trade-offs and protocol selection to concurrency models, service meshes, CQRS, observability, and failure isolation in production.