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Kafka consumer offsets help track message processing to avoid loss and duplication.

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.

Kafka's assign() method allows manual control of partition assignments for consumers.

Elasticsearch ILM automates index management to reduce storage costs and meet data needs.

Kafka uses different strategies to assign partitions to consumers in a group efficiently.

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

Kafka rebalance can lead to lost or duplicated work if not handled carefully.

The Bulkhead Pattern isolates resources to protect critical workloads from failures.

The CAP Theorem explains the trade-offs in distributed systems during network failures.