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

In distributed systems, timestamps don't always reflect the true order of events.

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

Elasticsearch uses distributed architecture to search data quickly across multiple servers.

Consistent hashing helps distribute data across servers with minimal movement.

Consistency models determine what data reads in distributed systems can see.

Quorum Reads ensure data consistency by querying multiple replicas in distributed systems.

Lamport Timestamps help order events in distributed systems while preserving causality.

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

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

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

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

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

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

ZooKeeper watches notify clients of changes, avoiding constant polling and reducing server load.

RPC allows one service to call a function in another service over the network.

Crash failures stop a service, while network failures disrupt communication.