Financial Services Target Architecture
Client Challenge
A financial institution faced severe response latency and data reconciliation mismatches in their core retail banking API layer. Their legacy system failed to scale during peak trading periods, causing transaction queue blockages.
System Architecture
Multi-region AWS setup using an event-driven pattern with Kafka streaming, Redis clustering for cache resolution, and PostgreSQL running with scoped Row-Level Security (RLS) policies. Deployed behind an isolated API Gateway layer with strict mTLS authentication.
Solution Implemented
We decoupled their legacy monolithic services into isolated Go-based microservices, implemented transactional queuing schemas to prevent double-charging risks, and built a real-time CDC (Change Data Capture) database sync pipeline.
Measurable ROI
Cost Reduction
Targeted infrastructure overhead reduction
Performance Gains
API Latency decreased to low-latency target levels
Before Integration
High Latency · Elevated error rate during peaks · Manual ledger checks
After Integration
Sub-second Latency · Negligible queue error rate · Real-time auto-reconciliation