Running both Claude and OpenAI in production sounds resilient—until a slow failure hits: latency climbs, 429s spike, quality drifts, and everything still looks “up.” This guide gives you a practical dual-stack degradation runbook: timeout probing first, circuit-based cutover second, and an error-budget dashboard to keep business impact bounded. ...
你在生产里同时接 Claude 和 OpenAI，最怕的不是单点故障，而是慢故障：超时变多、429 变密、质量飘忽，系统还“看起来活着”。 这篇给一套可直接落地的双栈降级方案：先做超时探测，再做熔断切流，最后用错误预算看板兜住业务节奏。 ...
If your production stack calls both Claude and OpenAI, the hard part is not API integration. The hard part is keeping user experience stable when one provider starts throwing 429/5xx spikes, regional latency, or timeout storms. This guide gives you a practical dual-provider gateway playbook: health probes, circuit breaking, SLA-aware fallback, and observability loops. The goal is not “never fail.” The goal is controlled failure with controlled cost and controlled latency. ...
当你的生产系统同时接入 Claude 和 OpenAI，真正难的不是“接上 API”，而是在故障发生时还能稳态服务。一个供应商偶发 429/5xx、区域波动或模型超时，都会把下游体验打穿。 这篇给你一套可直接落地的双供应商网关方案：健康探测、熔断切换、SLA 分级回退、以及可观测性闭环。目标不是追求“永不失败”，而是失败可控、成本可控、体验可控。 ...