Beginner7 min read
Messaging Fundamentals & Patterns
The vocabulary and patterns every broker shares: point-to-point versus publish-subscribe, competing consumers, acknowledgement modes, dead-letter queues and delivery guarantees.
Read tutorialEnterprise Backend · Phase 4
Messaging — RabbitMQ & Apache Kafka
Both brokers, properly. AMQP exchanges and routing, Kafka partitions and consumer groups, Spring AMQP and Spring Kafka, Kafka Streams, Connect, production operations — and a framework for choosing between them.
Beginner6 min read
RabbitMQ Architecture & Core Concepts
AMQP 0-9-1 from the ground up: the four exchange types and when each fits, queue properties, bindings and routing keys, prefetch and fairness, and publisher confirms.
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Spring AMQP & RabbitMQ Integration
Spring AMQP in production: RabbitTemplate and message converters, @RabbitListener containers, manual acknowledgement, retry with backoff, and a dead-letter topology that works.
Read tutorialAdvanced5 min read
RabbitMQ Advanced Patterns
Beyond basic queues: quorum queues and Raft, clustering and partition handling, federation and shovel for multi-datacentre, priority and lazy queues, and delayed delivery.
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Apache Kafka Architecture & Core Concepts
How Kafka actually works: the partitioned log, leaders and in-sync replicas, producer acks and idempotence, consumer groups and rebalancing, and offset management.
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Spring Kafka Integration
Spring for Apache Kafka in production: KafkaTemplate, @KafkaListener containers, JSON serialisation without trusting the wire, DefaultErrorHandler with backoff, and dead-letter topics.
Read tutorialAdvanced5 min read
Kafka Streams & Stream Processing
Stream processing without a cluster: KStream and KTable semantics, stateless and stateful operations, windowing, joins, exactly-once v2 and testing with TopologyTestDriver.
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Kafka Connect & Data Integration
Moving data in and out of Kafka without writing code: source and sink connectors, Debezium change data capture, single message transforms, and running Connect in distributed mode.
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Kafka in Production
Running Kafka for real: partition and cluster sizing, retention versus compaction, the metrics that predict incidents, the CLI tools worth knowing, and geo-replication.
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Kafka vs RabbitMQ — A Decision Framework
A practical comparison across throughput, latency, ordering, replay, routing and operational cost — with the use cases each one clearly wins, and when to run both.
Read tutorialIntermediate6 min read
Spring Cloud Stream & Message-Driven Services
One programming model over Kafka and RabbitMQ: functional bindings, destination configuration, per-binder tuning, dead-letter handling and the in-memory test binder.
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