Messaging terms
Decoupling systems through reliable, async communication
Asynchronous messaging decouples producers from consumers and makes distributed systems more resilient. This category covers message queues, pub/sub patterns, event streaming with Kafka, delivery guarantees, dead letter queues, and the architecture patterns that make event-driven systems robust at scale. When you need services to communicate without depending on each other's availability, messaging is the answer.
Apache Kafka Concepts
Kafka is a distributed log — producers append to immutable, ordered topics partitioned for parallelism, consumers read at their own pace and replay from any offset.
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At-Least-Once Delivery
At-least-once delivery guarantees a message is delivered to at least one consumer, possibly multiple times — consumers must be idempotent to handle duplicates safely.
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Backpressure
Backpressure signals upstream producers to slow down when downstream consumers can't keep up — preventing queue overflow, memory exhaustion, and system collapse under load.
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Consumer Groups
Consumer groups allow multiple consumers to process messages from a topic in parallel — each partition assigned to one consumer, enabling horizontal scaling without duplicate processing.
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Dead Letter Queue
A Dead Letter Queue (DLQ) captures messages that can't be processed — expired, malformed, or repeatedly failed — enabling later inspection and replay without losing data.
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Event Sourcing vs Messaging
Event sourcing stores all state changes as immutable events (the source of truth) — messaging delivers events between services. They complement each other but serve different purposes.
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Message Broker
A message broker is middleware that receives, routes, and delivers messages between producers and consumers — decoupling services and enabling async communication at scale.
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Message Idempotency
An idempotent message handler produces the same result whether called once or many times — essential for at-least-once delivery where duplicates are expected.
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Message Ordering Guarantees
Message ordering is only guaranteed within a single Kafka partition or RabbitMQ queue — multiple partitions or consumers break FIFO order across the full topic.
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Message Queue
A durable buffer that decouples the component producing work (producer) from the component processing it (consumer), enabling async processing, load levelling, and retry logic without direct coupling.
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Message Queue Patterns
Core messaging patterns — competing consumers, scatter-gather, request-reply, message filter, and routing slip — solve recurring distributed communication challenges.
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Message Serialization (Avro/Protobuf)
Binary serialization formats (Avro, Protobuf, MessagePack) are faster and smaller than JSON for high-throughput messaging — with schema evolution support for Avro.
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RabbitMQ Concepts
RabbitMQ is an AMQP message broker with flexible routing via exchanges — direct, topic, fanout, and headers routing enables complex message dispatch patterns.
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RabbitMQ Fundamentals PHP 7.0+
A message broker implementing the AMQP protocol — producers publish to exchanges, exchanges route messages to queues via bindings, and consumers pull from queues — providing flexible routing, acknowledgements, and dead-letter handling.
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Topics & Partitions
Kafka topics are divided into partitions — the unit of parallelism and ordering. More partitions = more parallelism; partition key determines which partition a record lands in.
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Event Bus Patterns PHP 7.0+
Patterns for routing events between publishers and subscribers — in-process event buses (Symfony EventDispatcher), message broker buses (RabbitMQ, Kafka), and hybrid architectures.
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Message Serialisation
JSON (readable, flexible), Avro (schema-enforced, compact, Kafka standard), Protobuf (typed, 5-10x smaller) — matching format to volume and schema requirements.
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PHP Queue Workers PHP 7.0+
Laravel Horizon for Redis queues with dashboard and auto-scaling; Supervisor for process management ensuring crashed workers automatically restart.
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Queue-Based Load Levelling
Using a queue between producers and consumers to absorb traffic spikes — producers enqueue at any rate, consumers process at a sustainable rate, preventing the backend from being overwhelmed.
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RabbitMQ PHP 7.0+ A message broker implementing AMQP — producers publish to exchanges, exchanges route to queues, consumers pull from queues — providing durable, reliable message delivery.
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