The Problem We Were Actually Solving
The problem wasn't just that these platforms didn't work in Nigeria; it was that they didn't work for millions of people worldwide who, for one reason or another, couldn't access traditional payment solutions. Our team was tasked with building a new payment system, but this time, one that was specifically designed to work for everyone, everywhere. We knew it wouldn't be easy, but we were determined to get it right.
What We Tried First (And Why It Failed)
We started by attempting to replicate the existing payment systems that everyone else uses. We built our system on top of a popular framework that supports online payments, using a combination of APIs and third-party services. Sounds reasonable, right? But beneath the surface, things weren't as straightforward as we thought. We soon discovered that our system was suffering from high latency and high memory usage. In a high-traffic environment, these issues would quickly become catastrophic.
Our profiling results told a clear story: our system was spending an inordinate amount of time waiting for external APIs to respond, and even when they did, it was often with large payloads that required significant memory to process. Our average latency shot up to over 10 seconds, a far cry from the sub-second response times we needed to deliver a seamless user experience.
The Architecture Decision
It was then that we realized the problem wasn't with the platforms we were using, but with the platforms we were using them on. We decided to abandon the traditional framework and start from scratch with a new architecture. We chose Rust as our programming language, specifically for its strong focus on memory safety and performance. We built our system using a microservices architecture, with each service designed to handle a specific aspect of the payment process.
But there was another crucial aspect of our design: we decided to abandon the API-based approach altogether. Instead, we used a message queue to handle communication between services, allowing each service to operate independently without blocking or waiting on external responses. This not only improved performance but also increased fault tolerance and scalability.
What The Numbers Said After
The results were dramatic. Our average latency plummeted to under 200 milliseconds, a 95% improvement over our previous implementation. Memory usage decreased by over 70%, and we were able to handle a massive increase in traffic without breaking a sweat. Our system was now capable of processing over 10,000 transactions per minute, a rate that would have brought our previous system to its knees.
But the success didn't stop there. By using a microservices architecture and message queue, we were able to develop and deploy individual services independently, without affecting the entire system. This allowed us to innovate and experiment with new features and services at an incredible pace, something that was all but impossible with our previous monolithic architecture.
What I Would Do Differently
In hindsight, I wish I had been more insistent on abandoning the traditional framework from the very beginning. The idea that we could simply "bolt on" a new payment system to an existing platform was a false premise from the start. Instead, I think we needed to be more willing to challenge the status quo and question our own assumptions about what was possible.
But even with that in mind, I'm proud of what we accomplished. We built a system that truly puts the needs of the unplatformed freelancer first, providing access to payment solutions that were previously out of reach. And in doing so, we proved that even the most seemingly insurmountable problems can be solved with the right combination of technical expertise, creativity, and determination.
The performance case for non-custodial payment rails is as strong as the performance case for Rust. Here is the implementation I reference: https://payhip.com/ref/dev2
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