Remember, the performance testing of streaming applications is much the same as performance testing for other uses. For data, it is therefore essential to have a sufficient data set. If an adequate data set does not exist, it will have to be created (for example with a replication of the production database or with the help of a tool for creating datasets).
Also, to obtain a more global view of the system tested to identify the points of contention, to observe the impacts of optimizations, or to communicate results, it is necessary to present the measurements collected in a comprehensible way. Since the purpose of the load-bearing tests is to determine the maximum permissible load continuously, it is logical that a lot of tests should be done. The tests will also depend on the number of virtual users. Thus, before starting any test campaign, it is imperative to automate as much as possible the whole chain of tests.
Indeed, there are different methods that can detect a performance problem on a web application. An essential part of running a load test is also to build a robust test environment that can replicate the real production environment. Indeed, the tools needed can generate an overhead that distorts the results obtained. Also, view this link for more data.
Remember, if you have to revise the architecture for a slight improvement, it may be better to look for another revision. To prune the outliers, it is also possible to reject the values that are beyond the defined limits where M is the mean, S is the standard deviation, and F is the sorting factor. Finally, I would say that a load test campaign should always be done thoughtfully.
In short, the targets of a load test will depend on the specific context and industry. Remember, a stress test looks at the behavior of the system in extreme conditions after reaching a target requirement, as defined by the load test. This determination can be made by linear regression between the execution time and the load. Also, view this link for more data.
The choice of scenarios must be made taking into account. What do we want to test? Indeed, it is these measures that must be exploited, and it is, therefore, necessary to make every effort to be representative of what we want to test.
Also, the reported metrics should be exploitable. Therefore, they should allow, for example, one to know the rate or the number of simultaneous users that a system can support and also the average response time compared to the amounts of concurrent users. Remember, we are embarking on a cycle of improvement, and it is, therefore, crucial to determine the purpose of these tests.
Therefore, to define targets is the first step during a load test. It is also in this phase that we are concerned with the approximation and aggregation of the metrics collected. However, it turns out that from time to time the cause of the performance problem is not so apparent as it seems.