Design a Distributed Unique ID Generator

To solve this for a high-scale environment like Tesla's vehicle telemetry, I would avoid a centralized database call for every ID generation. Instead, I propose a block-based allocation strategy. The system uses a lightweight local data structure: a pair of integers representing the current range [start, end] and a cursor pointing to the next available ID within that range. When an instance starts, it fetches a large block, say 10,000 IDs, from a coordination service. Locally, the instance simply increments its cursor. To ensure thread safety across multiple cores, we use atomic increment operations, such as std::atomic_fetch_add in C++ or compare-and-swap loops, guaranteeing no two threads return the same number even under heavy load. If the local cursor reaches the block limit, the instance triggers an asynchronous refill request to the coordinator. This approach minimizes network chatter, reduces latency to microseconds, and ensures global uniqueness because the coordinator strictly assigns non-overlapping ranges. This pattern is critical for systems requiring high throughput, such as managing unique identifiers for autonomous driving events or manufacturing parts.