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

Caching helps applications respond faster by serving data from memory instead of hitting the database.

Cache stampede occurs when many requests hit the database due to a cache miss.

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

Stateless servers are easier to scale because they don't store user session data locally.

Consistent hashing helps distribute data across servers with minimal movement.

API pagination helps manage large datasets by breaking them into smaller parts.

Database bottlenecks slow down performance, but identifying them helps optimize and scale effectively.

Scaling databases involves deciding whether to enhance read or write capabilities based on traffic patterns.

Sharding splits databases into smaller parts to improve performance and scalability.

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

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