This content originally appeared on DEV Community and was authored by Ray
Self-Hosted Stripe Billing Anomaly Detection with FastAPI
Billing anomalies are silent killers. Failed charges that go unnoticed, webhook delivery gaps, sudden MRR drops at 2 AM — by the time you see them in your dashboard, the customer is already gone.
In this post I'll walk through BillingWatch — a self-hosted FastAPI service that listens to Stripe webhooks and fires alerts the moment something looks wrong.
The Problem
Stripe's own dashboard is reactive. You find out about billing issues after they've happened, often hours later. What you want is a system that:
- Detects failed charges in real time
- Spots unusual refund spikes
- Alerts when subscription churn exceeds baseline
- Runs on your infrastructure (no SaaS subscription)
Architecture
Stripe Webhooks → FastAPI /webhook → Anomaly Engine → Alerts (WhatsApp / Slack / email)
The service is intentionally minimal — a single FastAPI app, SQLite for event storage, and a threshold-based anomaly detector.
Webhook Handler
from fastapi import FastAPI, Request, HTTPException
import stripe, os
app = FastAPI()
stripe.api_key = os.environ["STRIPE_SECRET_KEY"]
WEBHOOK_SECRET = os.environ["STRIPE_WEBHOOK_SECRET"]
@app.post("/webhook")
async def stripe_webhook(request: Request):
payload = await request.body()
sig = request.headers.get("stripe-signature", "")
try:
event = stripe.Webhook.construct_event(payload, sig, WEBHOOK_SECRET)
except stripe.error.SignatureVerificationError:
raise HTTPException(status_code=400, detail="Invalid signature")
if event["type"] == "invoice.payment_failed":
await handle_payment_failure(event["data"]["object"])
return {"status": "ok"}
Anomaly Detection
The anomaly engine compares current event rates against a rolling 7-day baseline:
def is_anomalous(event_type: str, window_hours: int = 1) -> bool:
recent = count_events(event_type, hours=window_hours)
baseline = avg_events_per_hour(event_type, days=7)
# Alert if rate is 3x above baseline
return recent > (baseline * 3 + 1)
This catches spikes in refunds, failed charges, and subscription cancellations without requiring ML infrastructure.
Running It
git clone https://github.com/rmbell09-lang/BillingWatch
cd BillingWatch
pip install -r requirements.txt
export STRIPE_SECRET_KEY=sk_live_...
export STRIPE_WEBHOOK_SECRET=whsec_...
uvicorn main:app --host 0.0.0.0 --port 8000
Then point your Stripe webhook dashboard at https://yourdomain.com/webhook.
Why Self-Hosted?
No per-seat pricing, no SaaS lock-in, full control over your alert logic. For indie developers and small teams watching burn rate, that matters.
Full source, Docker setup, and deployment docs on GitHub.
This content originally appeared on DEV Community and was authored by Ray
Ray | Sciencx (2026-03-27T15:22:50+00:00) Self-Hosted Stripe Billing Anomaly Detection with FastAPI. Retrieved from https://www.scien.cx/2026/03/27/self-hosted-stripe-billing-anomaly-detection-with-fastapi/
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