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Stream Processing Architecture helps turn incoming events into real-time insights efficiently.

CDC with Kafka allows real-time updates from databases to multiple services.

Kafka consumers can fetch data in batches to improve throughput and reduce latency.

Kafka allows safe message reprocessing by resetting consumer positions without altering data.

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

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

Monitoring Kafka consumer lag helps prevent production problems by ensuring consumers keep up with message traffic.

Kafka uses retries and Dead Letter Queues to manage message processing failures.

Backpressure helps manage message flow in Kafka during traffic spikes.