Event-driven Architecture with Red Hat AMQ streams and how it solves problems by reducing the coupling between services. • Schema types like JSON, protobuf, Avro. • Contract-based, event-driven architecture with Red Hat Service Registry and its capabilities.
Producer Consumer 1 2 3 1 2 3 Time-based message retention model by default Messages are retained according to topic conﬁg (time or capacity) Also “compacted topic” – like a “last-value topic” “Dumb broker, smart client” Client maintains position in message stream Message stream can be replayed Throughput up to 1 million mes./sec.
Producer Consumer Deserializer Serializer Service Registry | | | | | | | | | | | | | | | | | | | | | Apache Kafka Get or Register Schema by Id Retrieve Schema by Id Topic B (JSON) Topic C (Protobuf) Topic A (Avro) Send Serialized Data Retrieve Serialized Data
Hat AMQ Streams (AD482) Designing and developing event-driven applications using Kafka and Red Hat AMQ Streams. New course 56 LEARN MORE This course will be available next month, but the hands-on labs are available now in the Red Hat Learning Subscription. You can access the Early Access content by logging into your account and clicking the “Early Access” button in the top menu bar. If you’re not a subscriber, learn more about the Red Hat Learning Subscription.