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

ZooKeeper coordinates distributed systems using an ensemble of servers and the ZAB protocol.

Microservices are useful when you need independent scaling, deployment, and clear boundaries in software design.

Vertical scaling means upgrading one server, while horizontal scaling means adding more servers.

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

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

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

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

gRPC allows efficient communication between services using a structured request-response model.

Cascading failures occur when one service's failure impacts others, causing widespread issues.

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

Bully, Raft, and ZooKeeper are distinct algorithms for leader election in distributed systems.

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

Consistent hashing helps distribute data across servers with minimal movement.

Raft and Paxos are protocols that help computers agree on values in distributed systems.

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

Graceful degradation allows apps to function partially during service failures.

Vector clocks help track the order and concurrency of events in distributed systems.