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Distributed locks ensure only one server performs a task, avoiding duplication.

Message queues allow services to communicate asynchronously, improving scalability and reliability.

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

Choosing the right distributed lock depends on your system's needs and existing tools.

Distributed caching spreads data across multiple servers for better performance and reliability.

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

The Saga Pattern manages distributed transactions using local transactions and compensating actions.

Timeouts in distributed systems indicate suspicion, not confirmed failure.

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

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

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

Load balancers distribute traffic across multiple servers to enhance performance and reliability.

Availability is about access; reliability is about correct performance.

Database replication enhances data availability and read performance but has challenges like replication lag.

Microservices are useful when you need independent scaling, deployment, and clear boundaries in software design.

Queues distribute tasks to one consumer, while Pub/Sub broadcasts events to multiple subscribers.