Rebuilding the Payment System
Reduced payment processing time by 60% and improved reliability to 99.9% uptime
Overview
Led the complete rebuild of a legacy payment processing system handling $2M+ in daily transactions
Problem
The existing payment system was built 5 years ago and suffered from frequent timeouts, poor error handling, and a monolithic architecture that made it difficult to add new payment providers
Constraints
- Zero downtime migration required
- Must maintain backward compatibility with existing API contracts
- Limited to 3-month timeline
- Small team of 2 engineers
Approach
We adopted a strangler fig pattern to incrementally migrate payment flows to a new microservices architecture. Started with the lowest-risk payment methods and gradually migrated higher-volume flows after proving stability.
Key Decisions
Use event sourcing for payment state management
Event sourcing provides complete audit trail and makes it easier to debug payment issues. The append-only nature also improves write performance.
- Traditional CRUD with audit logs
- State machine with database transactions
Implement circuit breaker pattern for external payment providers
Prevents cascading failures when payment providers experience issues. Allows graceful degradation and automatic recovery.
- Simple retry logic with exponential backoff
- Manual failover to backup providers
Tech Stack
- Node.js
- TypeScript
- PostgreSQL
- Redis
- Kafka
- Docker
- Kubernetes
Result & Impact
The new system handles peak loads without degradation and has eliminated customer complaints about payment failures. The modular architecture has made it trivial to add 3 new payment providers in the months following launch.
Learnings
- Event sourcing adds complexity but the debugging benefits are worth it for financial systems
- Incremental migration with feature flags is less risky than big-bang rewrites
- Investing in observability early pays dividends when troubleshooting production issues
Additional Context
This project was particularly challenging because we had to maintain 100% backward compatibility while completely rewriting the internals. The strangler fig pattern allowed us to prove the new system worked before fully committing to the migration.
The event sourcing approach was controversial at first, but it proved invaluable when debugging complex payment flows and understanding exactly what happened during edge cases.