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Backup strategies include Full, Incremental, and Differential, each with unique benefits.

Cross-region database replication keeps databases synchronized across different geographical locations.

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

Database replication helps keep data available and allows systems to handle more read requests.

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

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

Log replication ensures data consistency by requiring majority acknowledgment before committing changes.

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

Quorum-based replication determines how many database replicas must agree for reads and writes.

Kafka uses replication and in-sync replicas to ensure data is always available.

Kafka commit strategies determine how offsets are managed during message processing.

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

Primary shards partition data, while replica shards duplicate it for redundancy.

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

matchIndex tracks what each follower has, while commitIndex shows what is committed.

Kafka consumer reprocessing involves safely replaying events to correct system states.