Ed Berezitsky is a Streaming Specialist Solutions Architect at AWS, where he helps customers design and implement solutions built on streaming technologies. His focus areas are highly available streaming architectures and disaster recovery for real-time data processing platforms. Before joining AWS, Ed built real-time data processing solutions with Apache NiFi, Kafka, and Spark, and helped customers optimize their high-scale big data systems.
Not every event-driven system needs Kafka, and not every message needs a queue. In this session, we break down the architectural decision between MQ message brokers and event streaming platforms (Apache Kafka). You’ll learn when point-to-point routing, dead-letter queues, and transactional messaging make queues the right choice — and when append-only logs, consumer groups, and replay capabilities demand a streaming platform. We’ll walk through real-world patterns including command vs. event separation, hybrid topologies, and migration paths from legacy brokers to streaming. You’ll leave with a decision framework to match your workload characteristics — ordering, throughput, retention, and coupling — to the right technology.
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