We'll learn about Spike testing in this section, which is an important aspect of software testing.
We also learn about its requirements, the objective of spike testing, why spike testing is necessary, the spike testing procedure, spike testing tools, and the benefits and drawbacks.
Spike testing is a type of performance testing that is used to assess software applications that experience significant load variations. Testing is an important aspect of the SDLC since it checks numerous software components such as speed, scalability, and dependability. Spike testing is used to analyze the behavior of software applications when there is a rapid increase or decrease in user load, as well as to determine the recovery time after a spike in user demand. It is used to determine the flaws in software applications.
It's a type of stress testing that ensures the built application works under increased and decreased demand caused by n-numbers. The system's performance is also monitored. It assures that no problems with software speed, consistency, or scalability arise after the product is delivered.
In other words, spike testing is used to see how well the system handles unexpected increases and user failure.
The following are the main goals of spike testing −
The main goal of performing spike testing is to determine if the system will crash or remain operational in the event of a significant load change.
To observe an application's performance or behavior when it is subjected to a sudden change in load.
To investigate the impact of recovery time between two points or spikes on performance. The time it takes to recover should be as short as possible.
Spike testing is a technique for identifying application flaws.
Spike testing is essential for determining how a system responds to an unexpected change in user load.
Continuous monitoring is required during the spike testing method. When the application's load is rapidly increased and reduced, it examines the application's vulnerability and checks its affected performance.
Spike testing is carried out in a controlled setting during the software development process. As a result, the spike testing method tries to maximize an application's capacity in order to ensure optimal user engagement.
The spike testing procedure is conducted in the phases listed below
Create a Test Environment
Determine the Max Load
Load the peak point to its full capacity.
Examine the performance at its apex.
Reduce the load to zero by applying the minimal load.
Examine the performance with the least amount of load possible.
Analyze the Performance Graph
Create a Test Environment Setting up the test environment, which is dependent on the many criteria in the business needs, is the first stage in the spike testing process. To run a successful test and recover a fair quality testing process, the test environment must be set up. We also make certain that no one is running spike testing in an application in the live environment.
Determine the Max Load The maximum load is launched once the environment has been set up; a system can prevent and detect the complete load size of the application or software product that has been built. The maximum load refers to the number of users utilizing the system or application at the same time.
Load the peak point to its full capacity The next phase will be to increase the load abruptly for a short period of time and then use any performance tools available to try to apply the maximum expected load to the peak point.
Examine the performance at its apex We shall analyze the performance discovered under the load on the peak point once the maximum load has been applied. It's used to see if the system fails or survives when the load is suddenly increased.
Reduce the load to zero by applying the minimal load. After that, we'll gradually reduce the burden till it's at its lowest point (zero to minimum load). The process is also completed quickly, reducing the load from the highest to the lowest attainable level.
Examine the performance with the least amount of load possible. In this step, we'll assess the system's performance at the bare minimum load to see if it can withstand or fail under this unusually low strain.
Analyze the Performance Graph In the final stage, the performance graph is analyzed by looking at measures such as virtual users, failures, and time-to-complete, among others. The test engineer needs to evaluate the performance graph in order to recognize when the program has crashed and report back to the developers so they can remedy the problem.
Spike testing scenarios include when an eCommerce store launches special bargains with steep discounts, such as on Black Friday.
When a web application streams a favorite TV show live.
When a daily deal site has a flash sale going on.
When a piece of material from a website becomes widely circulated via the internet.
A new system has been released for production, and some users want to adopt it.
All users may lose access to a system if there is a power outage. After the outage has been fixed, all users log back on to the system at the same time.
To protect against spikes, three basic recovery scenarios can be defined.
Use cloud platforms like Amazon Web Services and Microsoft Azure to dynamically boost server capacity in response to customer demand.
Allow just certain users access to the application so that the system does not become overburdened. This prevents persons who are heavier than the maximum designed load from entering the system. As a result, the system is protected from the threat of an excessive load.
Users can join the system with the permission of the site administrator. However, they should be warned that due to the excessive load, they may have poor response times. This could have a negative impact on the system's performance. The user, on the other hand, will be able to interact with the system.
There are a variety of spike tools on the market, some of which are open-source and others that are licensed. Each tool has its own set of features and approaches.
The following are some of the most often utilized spike tools −
The most well-known open-source tool for automation testing is Apache JMeter. It's mostly used to evaluate the performance of static and dynamic resources, as well as dynamic web applications.
It can simulate a heavy load on an object, server, or network to determine its overall performance under a variety of conditions. It enables developers or users to reuse the source code in the creation of new applications.
The following are some of the key characteristics of JMeter tools −
It is totally written in the JAVA programming language and is platform-independent when it comes to loading and measuring functional test behavior.
It keeps track of several testing methods such as availability, distribution, and load testing.
It has an easy-to-use, engaging, and straightforward user interface.
The performance test can be loaded on a variety of servers, which makes it quite versatile.
Another spike testing tool is LoadRunner, which supports a variety of protocols, technologies, and application parameters.
It instantly pinpoints the root reasons for performance problems. And accurately forecast the scalability and capacity of the application.
The LoadRunner utility has the following features −
While using the LoadRunner program, we may acquire extensive performance test reports.
The cost of distributed load testing is reduced if we use the LoadRunner tool.
Because the LoadRunner tool supports XML, we can easily inspect and manipulate XML data within test scripts.
It serves as an operational tool for tracking deployments.
The following are some of the key benefits of spike testing −
We can simply keep the system from crashing under the load spikes while performing spike testing.
The test engineer will be able to test the system under extremely high and low user loads using spike testing.
It is an advantageous testing method since it prevents the software application from failing or crashing.
Because the errors are found during spike testing, the developers can avoid application failure.
The most important benefit of spike testing is that it reduces the chances of the system or software application failing.
Spike Testing is the most appropriate testing method for evaluating software performance under such intense conditions.
It controls software performance and ensures a high-quality product.
It'll come in handy when we're recovering the worst-case scenarios.
The following are some of the drawbacks of not performing stability testing on the system in question −
Spike testing necessitated a separate testing environment.
Spike testing necessitates the creation of particular test circumstances, which increases the expense of the process.
The application's performance may deteriorate, slow, or halt entirely while executing a spike test.
When compared to other testing methods, it is a time-consuming process.
Spike testing can only be done by experts.
Spike Testing is a software testing methodology. Applications are tested using this method with odd load increments and decrements.
Spike testing should be done by abruptly increasing the number of users and then immediately decreasing the load.
The deal's key feature is the unexpected load.
When an eCommerce store launches special bargains with large discounts, such as on Black Friday, this is an example of a real-life Spike testing scenario. When a web application is live-streaming a beloved TV show, for example.
Jmeter is a great tool for performing spike testing.