distributed-systems

Distributed locks using Redis can be implemented via the Redlock algorithm and Lua scripts to coordinate access across services and prevent concurrent operations like double-charging. This Skill provides ready-to-use patterns for securing distributed transactions in Redis.

Circuit breakers with state machines and fallbacks are the best way to handle failing downstream services by stopping cascading failures. This Skill also includes bulkheads for tier-based isolation and retries with exponential backoff to manage resilience.

Idempotency keys ensure API requests are processed exactly once by using deduplication and database-backed storage to track processed operations. This mechanism allows clients to safely retry operations without causing duplicate side effects like multiple payments.

Yes, you can use PostgreSQL advisory locks and transaction-level locks as an alternative to Redis for distributed locking. This Skill provides implementations for both PostgreSQL and Redis, allowing you to choose based on your existing database infrastructure.

Token bucket and sliding window algorithms are available for rate limiting to protect APIs in distributed systems. These implementations use Redis to enforce request thresholds and prevent system overload from excessive traffic.