Load testing is the procedure where many users simultaneously run the same program. It is done to observe the system infrastructure, its durability, and functionality in terms of composability and performance. For example, a successful load test is one where multiple users can run a program simultaneously with zero compromises to the optimality of the program.
Load testing is an essential part of performance testing, often prone to being complex and causing errors if not undertaken aptly.
While performing load testing, there are 9 strategies and practices that are crucial to remember to ensure repeated mistakes don’t happen.
The first and most crucial step during performance testing is to establish the scale of the test required. Analyzing the application or program, configuring its characteristics, and then deciding the scale at which the test has to be conducted is critical to the optimum utilization of resources. So there is only a need to test an app on a large scale if it’s vital.
Therefore, strategic targeting and workload appreciation are essential to establish the test scale required. Higher traffic loads should be produced as opposed to lesser ones, which indicates more productivity. Considering this, companies need to test their day-to-day operations and workload on a priority basis as it yields more data than testing of peak times.
Finally, it is advised that developers spend time understanding and analyzing the workload and planning a solid foundation for the load tests.
Load tests that resemble IRL situations and scenarios help software developers understand reactions in a controlled environment. There might be more than this. Hence ensure that the tools’ scripts associated with these tests are manageable.
Optimizing testing tools is critical to ensure a monitored and highly controlled test is conducted. So the developer knows what the situation is and how the environment affects the application.
Information like time, run duration, monitors, amount figures, etc., can add unnecessary stress to the testing tool. Therefore, developers must ensure these data points are sorted before an unrealistic code is generated for the program or application. A poorly written script can cause improper correlation and lead to failed tests.
A load generator is a computer that runs virtual user tests. It is essential because it acts like an actual user and makes decisions according to the requests the developer inputs to increase the application’s flexibility. Another thing developers must be cautious of is whether the load generator is ready to sustain the necessary workload.
Finally, software testers and developers must ensure that unnecessary software is not present in the machines and that the generators are connected to networks with enough bandwidth.
The number of load generators and virtual users have a positive relationship – the more significant the number of virtual users in your tests, the higher the number of load generators that will be required. It is essential to know the readiness of these load generators to eliminate or, at the very least, minimize the risk of overutilization, which can lead to permanent reliability damage.
Think Time refers to the number of seconds a tester/developer wants the virtual user to wait.It is used to mimic the correct amount of workload that a real user might portray. For example, many companies prefer a think time over a sleep function, significantly reducing productivity.
Time is the most valuable resource in business, perhaps more than money. By not using the given time optimally and effectively, performance and load testing can take massive hits. By creating a more realistic and attainable performance test scenario, think time is projected in such a case that it actively helps to test the application further.
Monitoring and diagnosing are essential, especially when large-scale load tests are in question. Capturing diagnostics at a much more intrusive level allows developers to extract information that could make or break a load test and performance test result.
The captured data is monitored, leading to results that will enable reworking the coding of the tests. Without proper monitoring and diagnostics, the testing tool can get overwhelmed trying to collate all the excess information.
The best way to avoid such mistakes is by ensuring you don’t capture too much monitor data. By minimally approaching this data, the test is designed for optimal performance. Therefore, developers are advised only to capture data they know how to interpret and use later.
The longer the ramp-up and ramp-down times are, the better the application and its test will turn out. While this costs companies a lot of resources, such as time and money, it will ensure that virtual users’ unnatural log-in and log-out times don’t seem so strange anymore.
It is considered ideal to have a ramp-up time during a load test, as it takes time for the test to reach a steady state. So, the ramp time is vital as data such as response time, measurements, configurations, etc., are and should only be taken during the ramp-up and ramp-down time frame.
What exactly does workload schedule mean? It is how fast a tester plans to ramp up and down their virtual users.
This schedule adds another layer of security to the load test, ensuring the load generators are used efficiently. It positively impacts the load generators, adds a sense of timetable to be followed in case of unknown circumstances, and also results in a beneficial effect on the application, ultimately making the load test a success.
Workload scheduling ensures the workload event is properly planned out and there aren’t any accidental artificial bottlenecks.
Traditionally, software developers and testers have utilized HTTP-level virtual users for their load tests as they are compatible with load generations. GUI virtual users often consume more resources (memory, GDI resources, storage, time, etc.).
Graphical User Interface Virtual Users are also heavier than HTTP virtual users, leading to a more significant footprint. All this leads to a more user-friendly test, even in terms of artificial users. The easier the interface is, the easier the response to the test becomes, leading to fewer errors and a better outcome overall.
Since GUI users take up more resources, it is essential that the GUI User-Load Generator ratio is balanced and the generator isn’t overworked.
One of the most important steps or strategies to be followed during any load test is analyzing the load test data. This might seem an obvious step, but developers often need to remember this step’s importance.
The longer the test, the greater the number of captured data, leading to a greater need for a thorough analysis. Load testing has a result that is hugely data-heavy. Digging through these results to find relevant information can get quite challenging. The process is tedious but inescapable.
These nine strategies will help make your load testing experience smooth and effective. They will help you get maximum value out of your load tests and reduce unnecessary costs.
When it comes to testing, TestGrid is often the preferred tool used by most organizations. This is because of the many valuable benefits it offers. For example. one of the critical benefits of TestGrid is its capability to run tests concurrently on multiple machines, which can significantly reduce the time required for testing. Real-time monitoring and reporting enable users to track the testing progress and identify problems using this automation testing tool.