📄 中文摘要
在构建基于 LLM API 的产品时，开发者常常面临 API 请求限制带来的问题，例如 OpenAI 返回的 429 错误，导致产品瘫痪。尽管在分布式系统中，电路断路器、健康检查和故障转移链等模式早已得到解决，但许多 LLM 集成仍然只是简单的 API 调用，缺乏健壮性。作为一名 SRE，作者在构建 AI 产品时发现基础设施层的脆弱性，因此将以往在生产系统中积累的可靠性经验应用于此，旨在提升 AI 基础设施的稳定性和可靠性。
LLM API 的电路断路器：将 SRE 模式应用于 AI 基础设施
📄 English Summary
Circuit Breakers for LLM APIs: Applying SRE Patterns to AI Infrastructure
Building products on LLM APIs often leads to challenges such as encountering a 429 Too Many Requests error from OpenAI, which can bring the entire product down. While circuit breakers, health checks, and failover chains have been standard solutions in distributed systems for years, many LLM integrations still rely on basic API calls with minimal error handling. The author, an SRE with a decade of experience in building reliability into production systems, found the infrastructure layer for AI products to be surprisingly fragile and has applied proven reliability patterns to enhance the stability and robustness of AI infrastructure.