Why Do We Need Load Tests for Web Applications?
Retailer and e-commerce companies are entirely dependent on click rates. Whenever abandon rates go up, it has an adverse impact on their overall revenue. Therefore, successful organizations integrate load tests in their development chain to validate non-functional requirements, size their hardware accordingly, and understand the breaking points of their IT services.
The idea that “90 percent of all user interactions must be below two seconds” is a classic example of a non-functional requirement. Obviously, you can’t test this manually because you need to simulate the expected load and verify the 90th percentile response times for all user actions.
Another use case for load tests is to verify the sizing of the actual or required hardware. Companies cut IT costs and can no longer afford oversized machines. CPU and memory utilization during single user activities are typically minimal. In concurrent user situations, this looks completely different. Too high system resource utilization has an adverse impact on response times, and oversized hardware is too expensive. Load tests will help you to find the appropriate sizing.
From an operational perspective, it’s essential to understand how and when a service starts to fail under certain workload situations. There are spiky Black Friday load scenarios or permanent high usage figures which could lead to serious issues. The former needs more temporary capacity, while the latter has different demands and requires a permanent increase in capacity. Load tests are the only measure which gives you insights into these critical scenarios.
Load tests are an excellent investment, primarily because they help build trust in your IT services and give organizations confidence that the new or changed system performs within the agreed boundaries.
Application Load Testing Tools
Almost 30 years ago, the first web pioneers started with the development of load simulation platforms. Web pages were simple, and content was mainly static. With the rise of technology, many services are now are available online. Competition is high and businesses try to hold existing or gain new customers with even better services. One opportunity to improve service quality is to provide responsive and reliable applications.
In recent years new load test solutions have appeared in this growing market. Pioneers such as JMeter or LoadRunner were deployed on a company’s local machine. With the rise of cloud computing, some of them extended their service to SaaS or on-demand load testing platforms.
On-Premise Application Testing Tools
There are open-source and commercial on-premises load testing solutions that can be deployed on a customer’s local infrastructure. Open-source tools are free of charge, while commercial solutions charge initial license fees and deliver the software. The customer deploys updates on their local testing servers by themselves. If some load testing script or execution challenges occur, a support specialist can be involved to investigate and fix the identified issue.
On-Demand or SaaS Application Test Tools
Maintaining a local load testing infrastructure can be challenging, therefore, successful companies often switch to a cloud-based offering which avoids the pain of operating local load testing farms. The benefit is that there are no maintenance tasks or fees involved and the client only pays for the required service.
Best Practices for Load Tests on Applications
If you have no experience performing load tests, the chance is high that you will run into pitfalls and may not reach your goals. However, if you can avoid some of the difficulties listed below, and you will make a good step towards responsive and reliable IT services.
First, be sure to specify a realistic load pattern for your load test. You should not fully trust the given figures in non-functional requirement documentations. Even if an application is already in production, the chance is high that its usage has changed over time. For new services which are still not deployed on production, using Little’s Law to calculate the load pattern can be helpful. If there is already a productive environment and real customers are using the new services, then analyze the log files, derive user interactions per hour, and the number of concurrent sessions from these records. Consider actual average load, spiky Black Friday type loads, and future growth patterns in your tests.
Another hazard is choosing the appropriate user simulation. Open-source load testing solutions are notorious for providing limited simulation support. They often come up with protocol-based load generation. Consider a modern web-based application which loads its content while the user clicks through to the next page. A huge proportion of these activities can’t be captured on the protocol level because client-side processing is entirely left out. Therefore, carefully review your application under test conditions before you decide on the user simulation approach. Modern web applications typically require a real browser-based virtual user simulation technique.
Finally, be aware that performance is more a journey than a destination. The later you detect hotspots in your development chain the more reworking is required to fix them. Start with component or service-based load tests on development stages, consider daily test executions, use thresholds to identify breaking points, and switch to more sophisticated real user level simulation scenarios on QA stages once the application has been integrated with its surrounding systems.