advanced-patterns

Distributed locks in Redis are best implemented using SET NX EX, Redlock, and fencing tokens to ensure safe coordination across processes. These patterns prevent race conditions while maintaining atomic operations.

Build a Redis rate limiter using fixed window, sliding window, or token bucket patterns to protect APIs and resources. These approaches standardize reliability and regulate high-throughput workloads safely.

Use Redis Streams instead of Pub/Sub when you need event delivery persistence, job queues, or audit logs. Streams support reliable event-driven messaging and data pipelines, whereas Pub/Sub handles ephemeral broadcasting.

Implement cache-aside and write-through patterns in Redis by structuring data access to maintain consistency across microservices. These patterns provide production-ready design solutions for scalable data flows.

Yes, Lua scripts are required for atomic Redis operations when implementing advanced patterns like distributed locking and rate limiting. They ensure safe coordination and adherence to error-handling best practices.

Yes, these Redis patterns are explicitly designed for high-throughput workloads across microservices and data pipelines. They support distributed coordination and real-time processing using appropriate data structures.