Stream Processing Stack (Kafka, Flink, Schema Registry, Prometheus) overview

A real-time event streaming architecture for continuous data processing at scale. Apache Kafka serves as the durable, distributed event log while Apache Flink (or Spark Structured Streaming) provides exactly-once stream processing with event-time windowing, watermarks, and stateful aggregations. Confluent Schema Registry enforces Avro or Protobuf contracts between producers and consumers, preventing schema drift from breaking downstream systems. Prometheus and Grafana monitor consumer lag, pipeline throughput, and processing latency. This stack is ideal for fraud detection, clickstream analytics, IoT telemetry pipelines, and any workload where batch latency is unacceptable. The primary tradeoff is operational complexity — managing Kafka clusters, Flink checkpoints, and exactly-once semantics requires deep infrastructure expertise.