{
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  "_kind": "StackProfile",
  "_file": "domain/stack-profiles/deep-stacks-1.yaml",
  "_cluster": "domain",
  "attributes": {
    "displayName": "Stream Processing Stack (Kafka, Flink, Schema Registry, Prometheus)",
    "description": "A real-time event streaming architecture for continuous data processing\nat scale. Apache Kafka serves as the durable, distributed event log\nwhile Apache Flink (or Spark Structured Streaming) provides exactly-once\nstream processing with event-time windowing, watermarks, and stateful\naggregations.\n\nConfluent Schema Registry enforces Avro or Protobuf contracts between\nproducers and consumers, preventing schema drift from breaking\ndownstream systems. Prometheus and Grafana monitor consumer lag, pipeline\nthroughput, and processing latency. This stack is ideal for fraud\ndetection, clickstream analytics, IoT telemetry pipelines, and any\nworkload where batch latency is unacceptable. The primary tradeoff is\noperational complexity — managing Kafka clusters, Flink checkpoints,\nand exactly-once semantics requires deep infrastructure expertise.\n",
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