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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 maintains message order within partitions using keys for routing.

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

Kafka uses partitions to allow multiple consumers to process messages in parallel.

Apache Kafka is a system for managing large volumes of events efficiently.

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

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

REST API design focuses on creating clean, efficient, and scalable web services.

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

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

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

Consistent hashing helps distribute data across servers with minimal movement.

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

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.

The choice between SQL and NoSQL databases depends on your application's specific needs.

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.

Latency is the time for one request, while throughput is how many requests are processed.