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Message queues allow services to communicate asynchronously, improving scalability and reliability.

Queues distribute tasks to one consumer, while Pub/Sub broadcasts events to multiple subscribers.

Backpressure helps manage message flow in Kafka during traffic spikes.

The Transactional Outbox Pattern ensures database updates and event publishing are synchronized to avoid losing events.

Kafka uses retry topics and delayed retries to manage message failures efficiently.

Microservices can communicate using five key patterns based on their needs.

Message delivery semantics define how messages are sent in distributed systems and handle failures.

Backpressure prevents system overload by managing message processing rates in Kafka.

Distributed backpressure helps manage the flow of work between services to prevent overload.

Kafka uses Dead Letter Topics to handle messages that repeatedly fail processing.

Older offsets can overwrite newer ones in Kafka if not handled properly.

Classifying failures and using controlled retries in Kafka prevents outages.