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

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

Jitter helps spread out client retries to avoid traffic spikes.

Backpressure helps manage message flow in Kafka during traffic spikes.

Backpressure prevents system overload by managing message processing rates in Kafka.

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

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

The retry pattern helps systems recover from temporary failures but can cause overload if misused.

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

Kafka consumers can pause and resume message processing to handle backpressure effectively.