Skip to content

How to Design a Scalable Payment System to Improve Payments Infrastructure

Today, effectively managing a high volume of transactions is essential for any digital payment system.

It doesn’t matter if you’re running an online store, a subscription service, or a peer-to-peer payment app – being able to handle growing transaction numbers while maintaining first-rate performance is of top importance.

Scalability plays a key role in designing a payment system, ensuring it can easily adjust to meet user demands without sacrificing performance.

In this article, we’ll take a detailed look at the principles and best practices for building a scalable payment system that can easily grow with your business.

What Is a Scalability Attribute in Payment System Architecture?

In the context of software architecture, scalability refers to a system’s ability to manage a rising amount of work, data, or users without compromising productivity.

Practical Tips for High-Volume Payment Systems

A scalable architecture allows a system to adjust and efficiently expand, meeting the demands of a growing user base or an extending workload.

The need for scalable infrastructure appears from the ever-changing nature of modern applications and services. As businesses grow, the number of transactions and users accessing the system can increase exponentially.

And without a scalable architecture, the system may struggle to keep up with the increasing load, as well as experience slow response times, errors, and even system failures.

There are two primary types of scalability:

  • Vertical Scalability (Scaling Up): Involves adding more resources (CPU, RAM, storage) to an existing server or upgrading to more powerful hardware. This approach has limits and may be quite expensive in the long run. But it can provide a quick fix for systems experiencing short-term resource constraints.
  • Horizontal Scalability (Scaling Out): Involves adding extra servers or nodes to the system by distributing the workload across multiple instances. This approach allows for near-linear scaling and is more cost-effective in the long term since you will pay for additional infrastructure resources only when needed.

Understanding the Basic Payment Workflow and Creating User Scenarios

Before diving into the technical aspects of scalability, it’s essential to understand the basic payment workflow.

The basic payment workflow involves a series of steps when a user initiates a payment transaction. They are user authentication, payment processing, transaction recording, and confirmation.

By identifying these steps, you can create user scenarios that imitate real-world interactions and provide a foundation for scalability testing.

Here’s how you can create user scenarios for the payment system. Let’s take successful payment as an example:

  • User selects a product/service to purchase.
  • User logs in or creates an account.
  • User selects a payment method and enters valid payment details.
  • User submits the payment request.
  • System quickly ensures that the user account has enough funds to initiate a payment. More fast checks could be applied here – account limits, blacklist checks, etc.
  • User receives information that the payment is now processed
  • When the payment processor approves the transaction, the funds’ withdrawal is confirmed, user and merchant are notified about the payment status. This action is deferred in time because more time is needed for complex checks like fraud detection or communicating with a payment provider.

Setting up Non-Functional Requirements: DAU, Data Load, Latency

To design scalable payment solutions, it’s crucial to set up non-functional requirements.

Basic Payment Workflow & User Scenarios

These requirements define the system’s capabilities and performance features, essential for meeting user expectations and business objectives.

The three key non-functional requirements for a payment system are:

  • Daily Active Users (DAU): Estimate the number of active users your system will handle regularly. This will help you determine the expected load on the system.
  • Data Load: Understand the amount of data generated and processed by the payment system. This includes user profiles, transaction history, and other relevant information.
  • Latency: Define acceptable response times for different operations within the system. Low latency is vital for a good user experience.

Analysis of Integrations with SLA Provided. Getting Information About Provider Limits

A payment system often relies on third-party integrations, such as payment gateways and external services.

Analyze the Service Level Agreements (SLAs) provided by these integrations to understand their performance guarantees and limitations.

This information will help you identify potential points of failure and develop workarounds to keep things running smoothly.

Here are some steps to help you perform this analysis:

  1. Identify Integration Points: List third-party services used for payment processing.
  2. Obtain SLAs from Providers: Gather service-level agreements from providers.
  3. Evaluate Uptime and Reliability: Check provider uptime and reliability.
  4. Assess Response Times: Analyze provider response time commitments.
  5. Review Transaction Success Rate: Consider the success rate of transactions processed by providers.
  6. Check for Scalability and Limits: Verify provider capacity for handling the increased workload.
  7. Examine Security and Compliance: Ensure providers meet security and compliance standards.
  8. Consider Support and Documentation: Evaluate provider support and API documentation.

Finding Potential Bottlenecks. Creating a Scalability Plan for Persistent Storages, Compute Instances

Identifying potential bottlenecks is a crucial step in designing scalable payment solutions. Bottlenecks can arise at various points in the system and can hinder overall performance. However, the most common areas to focus on include:

  • Persistent Storages: Optimize database queries and consider database sharding or read replicas scalability to effectively distribute and serve data.
  • Compute Instances: Implement auto-scaling mechanisms to dynamically adjust resources based on demand and provide efficient utilization of compute power.

Implementing Scalability for Hot Spots Using a Wide Selection of Tools

To address scalability for hot spots (areas experiencing high load) in your payment system, consider the following tools and techniques: