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

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

Fallbacks allow systems to handle failures safely and maintain user experience.

Dependency failures can disrupt applications, but resilience patterns can help manage them.

Cache breakdowns can overwhelm databases, but request coalescing solves this issue.

Network partitions occur when servers are operational but can't communicate, affecting system performance.

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

Consistent hashing helps distribute data across servers with minimal movement.