Five Guardrails for Calling LLM APIs Reliably in Production Web Apps

A prototype LLM integration can fail in production through stalled endpoints that exhaust worker pools, malformed JSON wrapped in code fences, or runaway retry loops that inflate costs. The article recommends five safeguards for every model call: strict JSON schema enforcement, separate connect and read timeouts, jittered backoff with model fallback, deterministic prompt caching, and per-tenant token budget caps. It notes that LLM latency is far more variable than typical REST APIs, with p99 response times often reaching 18 to 35 seconds. The author's team routes all model requests through a hardened gateway service rather than letting controllers call provider SDKs directly.