We wanted to sell software licenses to customers in over 120 countries without any payment restrictions. The platform stores we had been using didn't allow direct sales in certain countries due to sanctions and regulatory compliance issues.

The Problem We Were Actually Solving

Our architecture was designed to handle the complexities of international payment processing, but the platform stores' limitations kept us from reaching a significant portion of the global market. Our revenue was stagnant, and we couldn't grow our customer base as much as we wanted. We had to decide whether to work around the limitations of the platform stores or create our own infrastructure to handle direct sales.

What We Tried First (And Why It Failed)

Initially, we tried using third-party solutions that allowed us to bypass the payment restrictions, but these solutions came with high transaction fees, which cut into our revenue margins. We also implemented workarounds to manually process payments from restricted countries, but this introduced errors and inconsistencies in our bookkeeping. The system was brittle and prone to failures, and our customer support team was overwhelmed with inquiries about payment issues.

The Architecture Decision

After months of struggling with the limitations of the platform stores, we decided to build our own infrastructure for direct sales. We chose a headless e-commerce architecture with a RESTful API for payment processing and a modern warehouse as the data storage layer. This allowed us to handle payments and bookkeeping in a centralized location, eliminating the need for third-party solutions and manual workarounds. We also implemented robust error handling and monitoring to ensure that our system could withstand the increased traffic and volume of sales.

What The Numbers Said After

Our pipeline latency decreased by 30% after the transition to our own infrastructure, allowing us to process payments and fulfill licenses in real-time. Our query cost on the warehouse decreased by 50% due to the improved architecture and data storage. We were able to hit an average freshness SLA of 5 minutes for our sales data, which gave us more accuracy and confidence in our business decisions. Our team experienced a significant reduction in support requests and errors, freeing up resources to focus on growth and innovation.

What I Would Do Differently

In hindsight, I would have started with a more incremental approach to building our own infrastructure. We should have begun by migrating a small subset of customers to our new system and monitoring their behavior and feedback before scaling up. This would have allowed us to identify and address potential issues earlier in the process. I would also have invested more in automated testing and CI/CD to ensure that our new system was thoroughly tested and validated before going live. By taking a more incremental and iterative approach, we could have minimized the risks and downtime associated with the transition and ensured a smoother experience for our customers.