Design a distributed rate limiter for a globally distributed API serving 100,000 requests per second. The system must support different throttling strategies (token bucket, leaky bucket) and allow for configuration changes in real-time without service restart. Discuss how you would handle synchronization, race conditions, and data consistency across multiple data centers. Provide a pseudocode implementation for the core logic using Redis Lua scripts to ensure atomicity.