Challenge

A global leader in accommodation management software encountered critical performance and scalability challenges as it expanded to serve a wider range of institutions, including universities and residential communities. The platform’s success depended on its ability to offer highly customisable configurations for each client, but this flexibility led to complexity. The system had to manage hundreds of database tables, and even minor changes—such as adding a new item—could severely impact performance due to dynamically generated queries.

The platform also faced seasonal spikes in traffic, particularly during peak times like university accommodation booking seasons. During these periods, thousands of users would log in and attempt to reserve rooms simultaneously. Traditional performance testing approaches were unable to adequately account for the varied configurations or scale to meet their growing user base. Hardcoded system limits, originally designed for smaller institutions, were now straining under increased demand.

Solution

To tackle these challenges, DiUS developed a custom performance testing framework to address the platform’s complex and configurable nature. Off-the-shelf tools were insufficient for handling the platform’s diverse configurations, so a synthetic data generation framework was created using advanced tools like Faker.js and Bogus. This solution enabled the team to dynamically generate data that mirrored each client’s specific setup, including different room types, customised access rules, and unique building layouts.

Using the k6 performance testing tool, the development team simulated thousands of users interacting with the system in real-world conditions. This involved booking rooms, navigating different modules, and adjusting to various configurations. By replicating actual usage scenarios, the tests provided accurate insights into how the system responded to high traffic loads and configuration changes.

Results

The customised testing framework delivered crucial insights into the platform’s performance, helping the company make significant improvements in three key areas:

• Query Bottlenecks: Dynamically generated queries were excessively complex, causing slowdowns. Optimising these queries improved response times.
• Hardcoded Limits: The tests exposed limits that couldn’t handle larger user bases, leading to system adjustments that improved scalability.
• Improved Scalability: By simulating real-world configurations, the team identified strategies to enhance performance and scalability, allowing the platform to accommodate high traffic without sacrificing flexibility.

These improvements have delivered a seamless user experience, particularly during critical periods of high demand, strengthening the platform’s reputation as a leading accommodation management solution. They have also future-proofed the platform for further expansion, ensuring it can continue to meet the growing needs of its diverse customer base.