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Database replication enhances data availability and read performance but has challenges like replication lag.

Read replicas allow databases to handle more read requests by distributing them across multiple copies.

Failover ensures systems remain operational by managing leader changes during failures.

Read-after-write consistency ensures users see their latest updates immediately.

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

Distributed locks ensure only one server performs a task, avoiding duplication.

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

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

The dual-write trap in Elasticsearch can cause data inconsistency during reindexing.

The Circuit Breaker pattern controls service calls to prevent failures from spreading.

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

Elasticsearch CCR allows real-time data replication for faster disaster recovery.