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Synchronous communication waits for a response, while asynchronous continues without waiting.

Synchronous replication waits for confirmation from replicas, while asynchronous allows faster writes without waiting.

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

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

Request-Response asks for a result, while Events notify that something has happened.

Kafka's commitSync waits for confirmation, while commitAsync continues immediately.

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

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

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

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

gRPC supports four communication patterns: Unary, Server Streaming, Client Streaming, and Bidirectional Streaming.

RPC allows one service to call a function in another service over the network.

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

The TCP 3-way handshake ensures reliable connection establishment between a client and server.

Kafka can help ensure messages are processed once, but requires careful design.

gRPC allows efficient communication between services using a structured request-response model.

Kafka consumers can use multiple threads to speed up message processing, but it complicates ordering and offset management.

Causality in distributed systems helps understand how events influence each other, beyond just timestamps.

Crash failures stop a service, while network failures disrupt communication.

REST, RPC, and gRPC are different methods for communication in software systems.

Jitter helps spread out client retries to avoid traffic spikes.