🏗️ Stripe processes hundreds of billions of dollars annually, handling millions of API requests per minute across 195+ countries. This document outlines the comprehensive architecture that enables Stripe to deliver reliable payment infrastructure with 99.999% uptime.

High-Level Architecture

Core Components

1. Payment Processing Pipeline

Stripe's core payment flow processes millions of transactions per minute.

Components:

PaymentIntent: Tracks payment lifecycle from creation to confirmation
Tokenization: PCI-DSS compliant card data handling
Radar: ML-powered fraud detection (prevents $25B+ in fraud annually)
Network Routing: Intelligent routing for optimal authorization rates

Key Features:

Idempotency for safe retries
Automatic card network selection
Dynamic 3D Secure authentication
Real-time fraud scoring

2. Subscription & Billing Engine

Handles complex recurring billing scenarios.

Billing Features:

Proration: Automatic pro-rated charges for plan changes
Usage-based Billing: Metered billing support
Trials: Free trial period management
Dunning: Smart retry logic for failed payments

3. Fraud Detection (Radar)

ML-powered fraud prevention system.

Radar Capabilities:

Network Effect: Learns from billions of transactions
Adaptive ML: Continuously updates with new fraud patterns
Custom Rules: Merchant-configurable rule engine
3D Secure Integration: Smart authentication triggers

4. Payout System

Distributes funds to millions of connected accounts.

Data Storage Architecture

PostgreSQL (Primary Database)

Database Practices:

Synchronous Replication: Zero data loss for transactions
Sharding by Merchant: Horizontal scalability
Connection Pooling: PgBouncer for efficient connections
Encryption: AES-256 at rest, TLS in transit

Redis (Caching & Queues)

Apache Kafka (Event Streaming)

Stream Processing Architecture

Temporal (Workflow Orchestration)

Durable Execution: Workflows survive process failures
Payout Workflows: Multi-step payout processing
Subscription Lifecycle: Complex billing state machines
Retry Policies: Configurable retry strategies

Scalability Patterns

1. API Rate Limiting

2. Idempotency

Idempotency Features:

24-hour key validity: Safe retries within window
Atomic operations: Prevents duplicate charges
Response caching: Consistent responses for same key

3. Geographic Distribution

Security Architecture

PCI DSS Level 1

Tokenization: Card data never touches merchant servers
HSM-backed encryption: Hardware security for keys
Annual audits: Third-party security assessments
Penetration testing: Regular security testing

API Security

Secret keys: Server-side only, never exposed
Publishable keys: Client-side, limited scope
Restricted keys: Granular permission control
Webhook verification: HMAC signature validation

Monitoring and Observability

Key Metrics

API Latency: p50, p95, p99 response times
Error Rates: 4xx, 5xx by endpoint
Payment Success Rate: Authorization rate by network
Webhook Delivery: Success rate and latency

Deployment and DevOps

Continuous Integration/Continuous Deployment

Infrastructure

Kubernetes: Container orchestration
Sorbet: Gradual typing for Ruby
Temporal: Workflow orchestration
Terraform: Infrastructure as code

Chaos Engineering

Chaos Practices:

GameDay Exercises: Quarterly disaster recovery drills
Dependency Failures: Simulated network/bank outages
Database Failovers: Automated primary promotion
Load Testing: 10x traffic simulation

Analytics and Machine Learning

Data Pipeline

ML Use Cases

Fraud Detection (Radar): Real-time transaction scoring
Authorization Optimization: Network routing for success rate
Risk Assessment: Merchant and account risk scoring
Revenue Recovery: Smart retry timing for failed payments
Anomaly Detection: System health and abuse detection

Cost Optimization

Key Strategies

Interchange Optimization: Intelligent card network routing
Reserved Capacity: Predictable baseline costs
Data Lifecycle: Automated archival for compliance data
ML Efficiency: Model optimization for inference cost

Future Architecture Considerations

Emerging Technologies

Real-time Payments: FedNow, RTP network integration
Cryptocurrency: Stablecoin and crypto payment support
Embedded Finance: Banking-as-a-Service expansion
AI/ML: Enhanced fraud detection and routing

Platform Evolution

Global Expansion: New payment methods and currencies
Vertical Solutions: Industry-specific payment products
Developer Experience: Enhanced APIs and tools
Compliance Automation: RegTech integration

Infrastructure Roadmap

Edge Computing: Reduced latency for global merchants
Green Computing: Carbon-neutral infrastructure
Zero-Trust Security: Enhanced security posture
Multi-Cloud: Resilience through cloud diversity

Conclusion

Stripe's architecture demonstrates how to build financial infrastructure at scale while maintaining the highest standards of security, reliability, and developer experience. The combination of robust payment processing, ML-powered fraud detection, and global reach enables millions of businesses to accept payments worldwide.

The platform continues to evolve with new payment methods, enhanced fraud prevention, and expanded financial services, all while maintaining the API simplicity and reliability that developers depend on.

There might be iterations needed, current data is as close I could get.

Stripe

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