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

Cassandra uses a masterless architecture to distribute and replicate data efficiently.

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

Monolithic and microservices architectures each have unique advantages and challenges for software development.

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

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

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

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

Consistent hashing helps distribute data across servers with minimal movement.

An API Gateway simplifies client access to backend services in microservices.

Elasticsearch has different node roles that help manage data and scale clusters effectively.

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

MongoDB uses sharding to distribute data across multiple servers for better scalability.

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

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