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Fail-stop means a system stops and stays down, while fail-recover means it can come back but needs to be ready.

Global failover ensures applications remain available by redirecting traffic from failed regions to functioning ones.

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

Dynamo-style databases are designed for high availability and fault tolerance in distributed systems.

Availability Zones help prevent downtime by isolating failures across multiple locations.

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

Cross-region database replication keeps databases synchronized across different geographical locations.

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

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

Graceful degradation allows apps to function partially during service failures.

Crash failures stop a service, while network failures disrupt communication.

Kafka Partition Reassignment moves replicas between brokers while keeping data safe.

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

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

Network partitions occur when servers are operational but can't communicate, affecting system performance.

The CAP Theorem explains the trade-offs in distributed systems during network failures.

Failover ensures systems remain operational by managing leader changes during failures.