Define standards for real-time streaming data processing, enabling continuous data flow, event-driven architectures, and low-latency analytics across distributed systems.
Event streaming protocols, stream processing patterns, windowing strategies, backpressure handling, exactly-once semantics, and integration with Apache Kafka, Flink, and Pulsar.
Stream producers/consumers, message brokers, processing topologies, state stores, connector APIs, schema registries, and monitoring dashboards.
Real-time analytics, IoT telemetry, financial trading, log aggregation, CDC (Change Data Capture), event sourcing, CQRS, and microservices communication.