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

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

Retry storms occur when too many retries overload a failing service.

Kafka can help ensure messages are processed once, but requires careful design.

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

Jitter helps spread out client retries to avoid traffic spikes.

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.

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

Timeouts in distributed systems indicate suspicion, not confirmed failure.