How I Built a Real-Time Stripe Webhook Anomaly Detector (Architecture + Code)

Stripe webhooks are the nervous system of any subscription business. When they work, everything is silent. When they break, you often don't find out until a customer complains — or your MRR drops. I found this out the hard way. A silent charge failure cascade wiped out $800 in MRR before I noticed. So I built a real-time webhook monitor. Here's the architecture and the key implementation patterns. The Core Problem With Webhook Monitoring Stripe sends events. You receive them. But "receiving" and "processing correctly" are different things. Common failure modes: Duplicate delivery — Stripe retries events aggressively. If your handler isn't idempotent, you get double-charges. Silent lapses — Payment fails, subscriber stays active, you don't notice for days. Webhook lag — Events pile up because your endpoint is slow or overloaded. Fraud spikes — Sudden surge in charge.failed events from card testing attacks. Negative invoice anomalies — Credits or refunds creating unexpected negative char