So many businesses are entirely dependent on click rates. Therefore, whenever abandonment rates go up, it hurts their financial revenue.
Bad user experience and slow loading services are critical reasons for reduced conversations, never returning customers, and lost business. In addition, research shows that the next generation is even more demanding towards user experience.
Successful organizations integrated load and performance testing into their software development process to detect and resolve user experience problems before impacting their customers.
Load and performance testing is an excellent investment, builds trust in your IT services, and gives organizations confidence that the new or changed system performs within the agreed boundaries.
The section below outlines the overall performance testing process, available tool support, and some best practices.
Several steps need to be considered when it comes to the implementation of an effective load testing strategy. This section provides insights into the most important aspects involved.
Business analysts and requirement experts specify the performance expectations for the new system. They outline regular and peak load patterns, including transaction rates, user volumes, and response time expectations.
Engineers review non-functional requirements and lay out what needs to be done to validate performance requirements. Next, create a test plan document, responsibilities, test data, environments, load patterns, relevant use cases, scheduled test runs, thresholds, and success criteria. Once this was done, they send this document out for approval.
For meaningful test results, the sizing of your load test environment should be close to production. Load and performance tests will be executed in exclusive slots to avoid the negative impact of background activities.
Engineers implement the necessary test scripts. Some load testing solutions provide a script recorder, allowing convenient test script creation without programming knowledge. The tester executes the use case manually while the recorder captures the interactions and creates the test script. However, with open-source tools, script implementation often requires programming skills.
Configure and Execute Test
The application owner enables system resource monitoring while test staff compiles their scenarios. They set up component-level tests to run daily and end-to-end load test scenarios on the fully integrated production-like environment.
After the test execution, the test staff collects all results, including response times and system resource metrics. In the best case, no performance criteria have been violated. However, your chance to identify bottlenecks is very high, and if this is the case, defects need to be raised, and the root-cause analysis starts.
If the response times are not acceptable corrective actions must be conducted. Engineers layout their test approach, discuss actual results with developers, infrastructure, database, network, and IT architect teams. Those virtual teams decide on tuning measures, implement corrective actions and repeat the load test to check if response times are already within acceptable boundaries.
Almost 30 years back in time, the first 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 online available nowadays. 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 appeared in this growing market. The pioneers, such as JMeter or LoadRunner, were deployed on a company’s local machines. However, with the rise of cloud computing, some extended their service to SaaS or On-Demand based load testing platforms.
There are open source and commercial on-premise load testing solutions deployed on a customer’s local infrastructure. While open-source tools are free of charge, the vendors of commercial solutions charge initial license fees and deliver the software. The customer deploys updates on his local testing servers by themselves. A support specialist can investigate and fix the identified issue if some load testing script or execution challenges occur.
On-Demand or SaaS
Maintaining a local load-testing infrastructure can be challenging. Therefore, successful tool providers switched 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 pays for the required service.
If you have no experience in load testing, the chance is high that you will run into pitfalls and don’t reach your goals. However, try to avoid a few difficulties listed below, and you will make a good step towards responsive and reliable IT services.
First of all, 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. I use Little’s Law to calculate the load pattern for new services that are still not deployed on show. Suppose there is already a productive environment and actual customers are using the new services. In that case, I 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, and future growth patterns in your tests.
Another hazard is the appropriate user simulation.
Especially open source load testing solutions provide limited simulation support. They often come up with protocol-based load generation. Consider a modern web-based application that loads its content while the user clicks already through the page. A considerable 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 before you decide on the user simulation approach. Modern web applications typically require an accurate 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 rework is required to fix those. It would be best if you 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.
Load and Performance Testing will remain a make-or-break criterion in 2021 and beyond as the battle for best-in-class user experience continues. The chances are that we see more modeling, Ai-powered performance analysis, and autonomous performance optimization. I am looking forward to these groundbreaking improvements.
Keep doing the great work! Happy Performance Engineering!