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

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

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

Availability is about access; reliability is about correct performance.

An error budget shows how much downtime is acceptable while meeting reliability goals.

The Bulkhead Pattern isolates resources to protect critical workloads from failures.

Timeouts in distributed systems indicate suspicion, not confirmed failure.

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

Database replication helps keep data available and allows systems to handle more read requests.

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

Classifying failures and using controlled retries in Kafka prevents outages.

Consistency models determine what data reads in distributed systems can see.