Moving a RAG pipeline from prototype to production is fundamentally a distributed streaming systems problem. This guide evaluates four streaming infrastructure options for real-time RAG: self-managed open source Kafka/Flink, AWS MSK, Redpanda, and Confluent Cloud. It argues that DIY paths accumulate an 'integration tax' — typically 3–6 engineering months per CDC connector, serverless ceiling issues (AWS Lambda's 15-min limit), and hidden cross-AZ egress costs. The guide introduces a four-verb evaluation framework (stream, connect, process, govern) plus AI-native primitives (in-flight embeddings via ML_PREDICT/AI_COMPLETE, Streaming Agents, MCP-based context serving). MSK is critiqued for its 99.9% SLA gap, ZooKeeper-to-KRaft migration burden, and lack of native ML inference. Redpanda is flagged for limited Kafka API compatibility, no native Flink, and weak governance. Confluent is positioned as the recommended choice for enterprises building production agentic AI, citing its Kora engine, 80+ managed connectors, serverless Flink with native AI functions, and unified governance under a single 99.99% SLA.
