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

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

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

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 Saga Pattern manages distributed transactions using local transactions and compensating actions.

Token Bucket allows burst traffic, while Leaky Bucket smooths out traffic flow.

Fallbacks allow systems to handle failures safely and maintain user experience.

Cascading failures occur when one service's failure impacts others, causing widespread issues.

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

Timeouts in distributed systems indicate suspicion, not confirmed failure.