Snowflake-style distributed ID generators are the industry standard for producing k-ordered, unique identifiers at scale. However, the traditional requirement for manually assigned or centrally coordinated worker IDs introduces significant friction in modern container-orchestrated environments (e.g., Kubernetes), where workloads are ephemeral and autoscaled. In such systems, maintaining stable worker identities requires complex stateful sets or external coordination services (e.g., ZooKeeper), negating the operational benefits of stateless microservices. This paper presents a cloud-agnostic, container-native ID generation protocol that eliminates the dependency on explicit worker IDs. By deriving node uniqueness deterministically from ephemeral network properties - specifically the container's private IPv4 address - the proposed method removes the need for centralized coordination. We introduce a modified bit-allocation scheme (1-41-16-6) that accommodates 16 bits of network-derived entropy while preserving strict monotonicity. We validate the approach across AWS, GCP, and Azure environments. Evaluation results demonstrate that while the design has a theoretical single-node ceiling of approximately 64,000 TPS, in practical microservice deployments the network I/O dominates latency, resulting in end-to-end performance (approximately 31,000 TPS on a 3-node cluster) comparable to classic stateful generators while offering effectively unbounded horizontal scalability.

翻译：雪花式分布式ID生成器是业界大规模生成k-有序、唯一标识符的标准方案。然而，传统方案要求手动分配或集中协调工作节点ID，这在现代容器编排环境（如Kubernetes）中引入了显著的运行摩擦，因为此类环境中的工作负载具有瞬时性和自动伸缩特性。在此类系统中，维持稳定的工作节点身份需要复杂的有状态集或外部协调服务（如ZooKeeper），从而抵消了无状态微服务的运维优势。本文提出一种云无关、容器原生的ID生成协议，消除了对显式工作节点ID的依赖。通过从瞬时网络属性——具体指容器的私有IPv4地址——确定性派生节点唯一性，所提方法无需集中式协调。我们引入改进的位分配方案（1-41-16-6），在保持严格单调性的同时容纳16位网络派生熵。我们在AWS、GCP和Azure环境中验证了该方法。评估结果表明：虽然该设计理论单节点上限约为64,000 TPS，但在实际微服务部署中网络I/O主导延迟，使得端到端性能（3节点集群上约31,000 TPS）与经典有状态生成器相当，同时提供近乎无限的水平扩展能力。