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

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

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

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

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

Kafka consumer lag shows how far behind consumers are from new messages.

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

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

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

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

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

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

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

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