redis

Distributed locking coordinates single-writer tasks across multi-pod deployments using the @RedisLock decorator. This prevents duplicate cron job execution by ensuring only one pod acquires the lock and performs the work at a time.

Cache invalidation for master data is handled through write-through invalidation patterns. When writes occur, related cached entries are automatically invalidated using the @RedisCache decorator to maintain data consistency across services.

Idempotency and short-term session data are managed via the RedisClientProxy for lightweight storage. This approach provides TTL control to automatically expire transient data without manual cleanup overhead.

Direct Redis client usage is supported when decorators are not suitable for your specific requirements. This allows manual control over caching, locking, and short-lived data operations where custom logic is needed.

Distributed locking coordinates work across distributed services where local locks fail. In multi-pod environments, local locks only protect single instances, while Redis-based distributed locks ensure single-writer execution across the entire cluster.