Payment Processing Backend

Payment Flow

Client -> Order Service -> Payment Service -> Payment Provider

• Idempotency-Key header prevents double charges
• Retry only on timeout/network, NOT card declined
• Webhook for async status updates

Scale

• 99.99% success rate
• p99 < 2s
• Strict idempotency
• Minimal PCI scope (tokenize)

Key Points

• Understanding Payment Processing Backend is essential for production systems
• Always consider scalability and maintainability
• Test thoroughly before deploying to production
• Monitor performance and set up alerting

Common Patterns

1. Validation: Always validate input at the boundary
2. Error Handling: Use structured error responses
3. Logging: Log key events for debugging
4. Testing: Unit, integration, and load tests
5. Documentation: Keep docs updated with code changes

Idempotency Implementation

@PostMapping("/payments")
public PaymentResponse createPayment(
    @RequestHeader("Idempotency-Key") String key,
    @RequestBody PaymentRequest req) {
  Payment existing = paymentRepository.findByIdempotencyKey(key);
  if (existing != null) return toResponse(existing);
  Payment payment = paymentService.process(req, key);
  return toResponse(payment);
}

Retry Strategy

• Timeout -> Retry (idempotent)
• Network error -> Retry with backoff
• Card declined -> Do NOT retry
• Provider error -> Check if charged, then retry or flag

PCI Compliance

• Never store card numbers - use tokenization
• Use PCI-compliant providers (Stripe, Braintree)

Tables

• payments(id, order_id, idempotency_key, amount, status, provider, provider_payment_id)
• payment_events(id, payment_id, event_type, payload JSONB)
• refunds(id, payment_id, amount, reason, status)

Reconciliation

Daily job to reconcile internal records with provider:

1. Fetch provider transactions for the day
2. Match with internal payment records
3. Flag mismatches for manual review

Key Points

• Understanding Payment Processing Backend is essential for production systems
• Always consider scalability and maintainability
• Test thoroughly before deploying to production
• Monitor performance and set up alerting

Common Patterns

1. Validation: Always validate input at the boundary
2. Error Handling: Use structured error responses
3. Logging: Log key events for debugging
4. Testing: Unit, integration, and load tests
5. Documentation: Keep docs updated with code changes