Payment Events at Scale: Building a Robust Kafka Event Bus π
When I joined the company, I was tasked with building a payment system from the ground up π³ β and from day one, the specs were clear: we were selling B2B plans, meaning real money from real businesses was on the line. We're talking plans that can go well over β¬10,000 for a single monthly payment β not the kind of transaction you want quietly dropping into the void. Every time a card payment was validated, an event needed to reach its destination β no exceptions. A single missed event could mean a lost invoice, an unpaid subscription, or a client questioning where their money went. And as you can imagine, when there's money flowing, events tend to pile up fast. Delivering these events couldn't just work most of the time β it had to work every single time, with robust retry mechanisms that never let a failure go unhandled. So we introduced an event bus π, ensuring every event was durably stored, reliably delivered, and resiliently retried on failure β‘. This post is about that journey: how to build a scalable and robust architecture to guarantee every payment event reaches its destination, no matter what π.