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

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

Causality in distributed systems helps understand how events influence each other, beyond just timestamps.

Physical time tells when events happen, while logical time tells their order.

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

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

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

Fail-stop means a system stops and stays down, while fail-recover means it can come back but needs to be ready.

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

Paxos is a protocol that helps distributed systems agree on one value despite failures.

Quorum and majority help distributed systems maintain data consistency and availability.

Raft consensus helps distributed systems elect leaders and replicate logs reliably.

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

Leader election helps distributed systems select one coordinator from many nodes.

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

Kafka Partition Reassignment moves replicas between brokers while keeping data safe.

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

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

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

Consistent hashing helps distribute data across servers with minimal movement.

Leader election ensures a single node coordinates tasks in distributed systems, even after failures.