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

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

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

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

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

Jitter helps spread out client retries to avoid traffic spikes.

Backpressure helps manage message flow in Kafka during traffic spikes.

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

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

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

Elasticsearch has different node roles that help manage data and scale clusters effectively.

Exponential backoff helps manage retries by increasing wait times to reduce system overload.