Razorpay engineering

15 stories· engineering.razorpay.com

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How We Deploy Reliably at Razorpay
Razorpay

Most production incidents do not begin with a server dying. They begin with a deployment: dozens a day, across hundreds of services, each the moment risk enters the system. We run payments infrastructure at Razorpay. When a payments system degrades, transactions fail: merchants…

Inside Razorpay’s RTO Model: The Engineering Behind its ML Lifecycle
Razorpay

Contributor: Abhik Debnath In this article, we use Razorpay’s Return to Origin (RTO) risk model to explain the ML lifecycle: how we build a reproducible release, deploy it into checkout, monitor its behaviour, and use later outcomes to evaluate whether it needs retraining. We…

Five Years of Kafka at Razorpay’s UPI Switch
Razorpay

Preface The UPI Switch at Razorpay has evolved significantly in the five years since we started building it. The Switch is the platform that enables real-time payment processing with NPCI. When the team began, it was little more than an idea. Today it powers more than 70% of…

CI Doesn’t Need On-Demand: Moving Our Build Pipelines to Spot Instances
Razorpay

Contributors: Guptaanuj CI/CD pipelines have always had a money-vs-stability problem. Run on-demand AWS instances and your build infrastructure is rock solid, expensive, and predictable. Run on spot instances and your costs drop 70–90%, but AWS can pull the rug with 2 minutes of…

How We Refresh Razorpay's Data Warehouse 10x Faster with Graphs and Indexes
Razorpay

Contributors: Utkarsh Koppikar Rohan Background Razorpay provides the payment infrastructure for millions of merchants globally. Behind every payment, settlement, and refund is a microservices architecture where each service owns its own database. While this keeps services…

Running Hermes at Razorpay: a Network-isolated, Self-improving “Second Brain” for every Employee
Razorpay

How we run a personal AI agent for everyone at Razorpay: always on, multi-model, and safe by construction. Contributors: Siddharth Tripathi Today, more than 220 Razorpay employees each have their own always-on AI agent. On a typical day, about 84 of them are actively working.…

Turning Scattered Data Into Queryable Segments at Scale: How Razorpay Built Its Customer Data…
Razorpay

Turning Scattered Data Into Queryable Segments at Scale: How Razorpay Built Its Customer Data Platform A consent-native CDP that serves audience segments across 500M+ user profiles in under 30ms, with PII isolated to the source systems. The Problem We Were Solving A customer…

Razorpay Oncall Agent: From 30-Minute Investigations to 90-Second AI Analysis
Razorpay

Our on-call engineers were spending 30 minutes investigating every production alert. Here’s what happened when we automated it. At 3 AM, alerts don’t care about your sleep schedule. When our payment infrastructure threw an error last month, our on-call engineer spent 32 minutes…

Building a Multi-Provider Rewards Platform: An E-Commerce Approach to Rewards at Scale
Razorpay

We built a multi-provider rewards platform using e-commerce patterns. Here’s why that matters. You’re running a loyalty program. Customers are redeeming points for gift cards, ongoing offers, memberships, or experiences. Then your provider’s API times out. You refresh. Try…

Our Obsession with Merchant Experience: Breaking the Risk Review Black Box
Razorpay

Contributor : Yashshree Shinde When merchants couldn’t see why their funds were on hold, trust broke down. Here’s how we rebuilt the entire experience. You’ve shipped your products, paid your delivery partners, and you’re waiting for settlement. Then you receive a notification:…