Perils of Load Testing: Common Mistakes and How to Avoid Them
Load testing is a type of performance testing that examines an application's performance under expected, real-world load. Although it may be difficult to perceive the value of performance testing, it is just as vital as other types of testing. Slow apps, time-out issues, and dissatisfied users are the effects of underperforming programs. Users expect speed and quick loading times. Therefore, this is especially problematic for businesses. Thus, organizations need to treat performance testing as a higher priority.
What is Load Testing?
The process of running software or applications through both typical and projected peak loads to gauge their responsiveness under such circumstances is known as load testing, which is a component of performance testing. It enables you to spot flaws such as load balancing and capacity problems and assess response times, throughput rates, and resource usage level concerns before deploying to production.
Advantages
Load testing raises the level of security. It aids in the process of detecting performance problems early and creating a scalable infrastructure.
Disadvantages
Tools for load testing call for specific technical expertise. Moreover, many load testing tools require you to purchase a license or pay a fee. Additionally, load testing might consume additional resources and produce spurious performance issues if configured incorrectly.
Common Load Testing Mistakes and How to Avoid Them
Overloading load generators
Load generating devices might potentially bias the findings of your tests even while supporting your testing objectives. For example, there may be no load created at all or load generated, and the skewed results might be due to an overloaded load generator machine. Check machine resources like CPU, RAM, context switches, and transactions per second to determine whether your load generators are overburdened.
How to avoid it
Softwares that are no longer needed should be removed from your computers. You need to verify the network connectivity and bandwidth of the generators, among other things. You will need a lot of load generators if you plan to run a lot of virtual users. The test's success depends on reliable connectivity between the various parts of the testing instrument you are using.
Not documenting test runs
Load testing includes re-running scenarios and comparing outcomes between runs. However, keeping track of the changes performed throughout each test session can become impossible if this is done repeatedly while modifying parameters, application versions, and test settings. Make sure to record details such as the goals of each scenario, the precise configurations of the system being tested, the test environment configurations, the outcomes, and the conclusions of each scenario run.
How to avoid it
These reports should make it evident whether the current version of the application satisfies the minimum performance requirements and how much load the server is bearing during each testing phase.
Avoid excessive logging
The configuration of the various load-testing instruments in use offers a variety of logging options at different levels. They provide options for logging HTTP responses and informative messages about script activities, parameter substitutions, warnings, and errors.
How to avoid it
Keep logging as little as possible when the performance test is actually being run. The resource usage of load generator devices will grow as the amount of logging increases. Failures of load generators are typically caused by intensive tool logging.
Using hardcoded data in requests
Many performance experts write programs with parameter values that are hardcoded. These identical queries are frequently recognized by more intelligent apps and existing database technology, which then starts automatically caching them. It will have the effect of making the system as a whole appear faster than it is—an invalid performance test results from this. One product page might not function exactly like every other product page on the website, which is the issue.
How to avoid it
Although you don't always need to use changeable parameters, it's vital to consider scenarios where the performance can change.
Focusing too much on response times
The most obvious load test statistic is response times, but that isn't the only factor to consider. If an application has a high error rate, fast reaction times aren't all that important. Effective performance tests track a wide range of data to comprehensively understand how an application responds to various loads.
How to avoid it
Helping developers identify performance issues is equally crucial. After all, it's useless to inform a developer that the checkout procedure takes too long without also informing them of the problems that occurred during the specific steps.
Conclusion
No test or simulation can eliminate the possibility of a site failure entirely. Even the world's most resilient and scalable websites are susceptible to black swan events that occasionally bring them down. However, your chances can be significantly increased with some testing in the appropriate areas.