earticle

영어

As the web game market grows, ensuring service stability through load testing has become increasingly important. Web games comprise a variety of functions with distinct internal logic, ranging from simple data retrieval to complex transaction processing. Therefore, a comparative performance analysis of load-testing tools that accounts for these functional characteristics is crucial for achieving reliable and efficient service operation. This paper evaluates the performance of four widely used load-testing tools—JMeter, k6, Gatling, and Locust—under representative web-game workloads. To emulate realistic database read and write patterns, we implement the core server logic of the web game Pokerogue in a cloud environment rather than simply issuing HTTP requests. We classified workload patterns into write-intensive, read-intensive, and mixed types using distributed tracing, and measured request-generation capability and system resource consumption across five key game functions. Our experiments show that each tool demonstrates distinct strengths depending on the characteristics of individual web-game functions. Specifically, k6 demonstrated high request-generation performance in write-intensive scenarios, while JMeter showed strong performance in read-oriented tasks; Gatling exhibited efficient memory usage in mixed workloads, whereas Locust proved suitable for resource-constrained environments. These results indicate that the selection of a load-testing tool should be informed not only by its request-generation performance but also by the workload characteristics of the target game function. By systematically analyzing function-specific workload patterns together with the performance and resource-usage behavior of each tool, this study aims to provide empirical evidence that can be usefully applied in practical load-testing workflows for web-game services.