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

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

Backpressure helps manage message flow in Kafka during traffic spikes.

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

Jitter helps spread out client retries to avoid traffic spikes.

The Token Bucket algorithm helps manage how many requests a server can handle.

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

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

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

Partial failure means some services fail while others keep running, impacting system reliability.

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