Backend Architecture for Commerce: Monolith vs. Serverless
A recent podcast explores the trade-offs between monolithic and serverless architectures for applications like commerce platforms. A monolithic structure is described as ideal for early-stage projects needing rapid iteration, while a serverless, event-driven model offers better scalability and cost efficiency for handling variable traffic, such as UPI payment spikes.
- A key advantage of a monolithic architecture for an early-stage venture is lower initial cost and complexity; a single codebase reduces the DevOps burden and makes it easier for small teams to build and deploy a Minimum Viable Product (MVP) quickly. - Serverless architecture's pay-per-use model is particularly cost-effective for handling the unpredictable traffic of a growing commerce platform, where you only pay for compute resources during active transactions. In contrast, a monolithic application often requires provisioning servers for peak load, leading to higher costs from idle capacity. - The ability of serverless to automatically scale is critical for handling payment spikes common in the Indian market. As of January 2026, UPI transactions averaged 70 crore daily, with surges during festivals or sales that can strain traditional server infrastructure. - As a monolithic application grows, its tightly coupled nature can become a liability; one Indian e-commerce integration platform with a monolithic design began to crash daily until it was re-architected into a modern, event-driven system, which resulted in near-100% uptime. - While serverless excels at scalability, it can introduce development complexity in managing distributed components and requires advanced skills for debugging. A monolith's unified structure makes initial debugging and testing more straightforward since the entire system operates in a single environment. - The choice is not always a one-way path to serverless. In a notable case, Amazon's Prime Video team migrated a component from a serverless and microservices model back to a monolith, which reduced their infrastructure costs by over 90%, demonstrating that the optimal architecture is highly dependent on the specific use case.
