Types of Performance Testing: Which One Does Your Software Need?

What if you have spent months designing & developing an application, and now it’s the release day, but you notice your app is crawling & crashes under extreme pressure? So, do you still want to release that app & make your users frustrated? It seems your time and efforts are wasted in a matter of seconds. Well, in the tech world, this scenario was completely normal earlier, but now the industry has changed! Thanks to the various types of performance testing that can measure your app’s success.

Based on the reports released by Statista, you can find approximately 1.68 million applications on the Google Store, but only the best-performing apps get popularity. At this time, fulfilling user expectations is in high demand, and businesses are putting multiple efforts into serving the best.

Performance testing is not about finding and resolving errors. It is about understanding how your application works under various conditions. This post consists of a brief on performance testing & its types. At the end of this blog, you can decide which types of performance testing work best for your application.

What is Performance Testing?

Performance testing is a method of quality testing to track applications’ behavior. The performance testing mostly aims to analyze the performance benchmarks rather than uncover the application errors. Besides, it comes as an important process in SDLC.

Once the software has been designed & developed, it must match the number of performance requirements that improve the organization’s performance. The testing makes a product ready for release by ensuring its quality. In the below section we have mentioned various types of performance testing in software testing with examples.

The importance of performance testing is to decide the processing speed, network bandwidth, amount of maximum users who can access, workload efficiency etc.

Why It Matters for Applications?

Here, discover some more reasons for running different types of load testing.

• User experience: This testing assists in measuring the issues that could negatively impact the customer experience, such as poor loading time and user interface.
• Business impact (downtime, revenue loss, etc.): The testing helps to address the negative impact of organizational operations that cause revenue loss & increase downtime.
• Ensuring scalability and reliability: performance testing assists in identifying the errors, understanding the system limits, and addressing the issues earlier. This is how it ensures reliability & scalability.

Also Read : Performance Testing in AEM: Tips for Superior Performance

What Are the Different Types of Performance Testing?

To prevent system breakdowns and make sure that new features function properly, it is crucial for developers and QA engineers to carry out different types of performance testing.

However, the functions of various performance testing services vary based on the types.

1. Stress Testing

✦ Purpose:

The aim of stress testing is to track the behavior of the software under extreme conditions. It is designed to evaluate when your software fails. Furthermore, it assists you to understand the system limits & further helps to plan for improvement.

✦ When to Use:

It is used to prepare for unexpected spikes in traffic, for example, peak shopping days, during sale hours & viral campaigns. It is performed to ensure the app doesn’t break under pressure.

✦ Tools: Here are some types of load-testing tools you can use-

1. Gatling: This is another performance testing open-source stress testing tool for testing web applications & other software systems.
   NeoLoad- This tool also helps analyze the software performance and response time during peak hours.
2. BlazeMeter: This cloud-based stress testing tool integrates with CI/CD tools to offer real-time reports for measuring errors and performance optimization.

✦ Example:

Now it’s time to understand types of performance testing with examples. In stress testing, derive the performance of the system & its stability under the high peak by conducting stress testing. Monitor system stability, error handling & recovery time.

✦Use Case:

Stress testing is used to detect how the software performs under extreme load. It helps to identify the potential error, performance issues & weaknesses. Some real-world examples are e-commerce apps during sales, news websites, and education board results.

2. Spike Testing

✦ Purpose:

Spike testing is another type of software performance testing that verifies the application has enough potential to perform seamlessly under a massive rush. Spike testing is beneficial when the system experiences sudden traffic. Failure in the system during peak time can lead to downtime, damage the brand revenue & make customers unhappy. The spike testing goal is to manage the spike without getting crashed.

✦ When to Use:

Testing is essential when you expect any sudden increase in traffic. Spike testing verifies that the system can handle sudden increments in traffic. Businesses should perform such testing before any crucial promotional events.

✦ Tools: Here are some types of performance testing tools you can use-

1. Jmeter: This open-source tool is designed to measure the load functional test & performance of test behavior. It analyzes the performance of web applications.
2. Loadrunner: This open-source tool assists in effectively evaluating the app performance and output under heavy load. It aims to track the software during unexpected spikes.
3. Loadview: This cloud-based platform tests web APIs & servers to generate GET & POST requests. This tool aims to stimulate the necessary functionalities & user behavior.

✦ Example: Here are a few examples of spike testing in real-time scenarios-

• When any customizations are performed in the existing applications, many users are excited to explore the application at the same time after release.
• A website or web page where a specific material goes viral instantly.
• There was a sudden increase in user activities on entertainment channels during the World Cup.
• Any e-commerce platform that releases unexpected deals on special occasions.
• In case of a power outage & server failure where users lose access.

✦ Use Case:

• Spike testing is utilized to prepare for events such as flash sales, product launches & promotions.
• Spike testing is used to see how the system handles new features when all users start involving themselves.
• It is also beneficial to evaluate how the software will perform if there is a power outage.
• Spike testing assists in identifying the potential errors that cause failure & production crashes. It quickly allows the software to scale up with industry demands.

3. Endurance (Soak) Testing

✦Purpose:

So, what are the different types of performance testing expected above? Here comes the Endurance testing or soak testing. This is used to determine how a system works under extreme stress. It aims to verify the software has the potential to withstand all conditions without any issues. This is performed to track small issues such as system crashes, slowdowns & transaction issues. Any issues found should be instantly addressed.

✦ When to Use:

Soak testing is necessary for apps that are expected to run frequently. It is used in databases and web servers where downtime is not accessible. It is utilized during new software releases, system upgrades, and peak usage periods. Soak testing measures the stability and performance of any software under sustained pressure. When significant customizations happen in any software, it is suggested that this testing be performed to validate that the upgraded system can handle user activity.

✦ Tools: Here are some types of endurance testing tools you can use-

1. WebLoad: This performance testing tool enables organizations to measure the reliability, scalability & complete performance of web apps under extreme load.
2. Load runner: This performance testing tool defines how virtual users are interacting with the software & what performance errors it shows.
3. Apache JMeter: This open-source tool enables the testing team to develop & execute test plans for simulating the heavy loads on databases, APIs & other services.

✦ Example:

In software development, sometimes the developer may write vulnerable code. In this testing methodology, the testing team will run system execution for a specific amount of time by offering a specific quantity of load to test the memory leak.

Understand this by the real-life example of a bank. So, suppose banks won’t work for 7 to 8 days due to any unforeseen conditions, and now the online banking activities are at a peak compared to the regular days. So, it’s necessary to ensure the software is ready to handle the sudden load of users and multiple operations.

✦ Use Case:

• Endurance testing aims to evaluate types of bottlenecks in performance testing. It determines how well an application can handle a large amount of traffic over a long time. The aim of this testing is to evaluate the issues that arise when using an app for an extended time.
• During the testing strategy, the system is monitored & if any issues are identified, then it is reported & quickly addressed by the team.
• It is utilized for the production environment since it assists in tracking the issues that may not immediately appear.
• By running this testing, you can discover the errors & capacity limits and resolve any issues found to ultimately raise the system performance.

4. Scalability Testing

✦ Purpose:

The following types of performance testing are necessary to check how well the software manages the increased workloads & data volume. This is the type of non-functional testing that has the objective to evaluate whether the software can scale up & down when maintaining the performance. The objective of scalability testing is to identify the performance error when changes in traffic occur.

✦ When to Use:

This is useful for an app that experiences fluctuations in user activity, like during peak usage. Furthermore, it is necessary to ensure the application can handle the increase in user interactions without hampering its performance.

✦ Tools: Here are some types of scalability testing tools you can use-

1. NeoLoad: with this cutting-edge tool, businesses can make the performance testing from the APIs to end-to-end application testing easier.
2. Apache Jmeter: This is an open-source tool for scalability & performance testing. Moreover, it supports distributed testing & measures the web app and database performance.
3. LoadRunner: This is the most used performance testing tool for scalability testing. This tool measures the app performance and stimulation of virtual users & tracks errors.

✦ Example:

The example of scalability testing involves the simulation of a huge amount of users accessing the web app simultaneously to observe how a system deals with the improved load. Suppose the social media platforms are designed for thousands of users.

✦ Use Case:

• Social media platforms face huge fluctuations in user traffic during peak hours. Furthermore, it ensures the platform can manage the user interactions & media upload without hampering the performance.
• Cloud service also has a variety of demands, and through scalability testing, businesses can ensure their reliability.

5. Volume Testing

✦ Purpose:

The goal of volume testing is to ensure that the software hasn’t suffered any data loss in high website traffic. This testing goal is to measure the response time, verifying the data integrity & system crashes in unexpected loads.

✦ When to Use:

This testing aims to measure how the app manages the vast datasets. The testing team suggests performing this testing before the major deployments during the optimization of performance. However, it is also suggested that this be run along with regression testing.

✦ Tools: Here are some types of volume testing tools you can use-

1. HammerDB– This load-testing tool supports multiple databases like SQL server, IBM, MySQL, etc. Moreover, the tool is completely free and supports Windows & Linux.
2. jdbcSlim- The open-source tool is available on GitHub. Moreover, the tool assists organization users in understanding the need that is independently written for implementation.
3. DbFit- This open-source tool is for automated database testing and supports Oracle databases, MySQL, etc.

✦ Example:

The most common volume testing examples are when the product & user database on the site increases. When a business wants to determine if the infrastructure can handle anticipated data quantities, it can choose volume testing. It also aids in anticipating any database modifications or infrastructure requirements. It ensures that the system functions normally and doesn’t crash even with an excessive database load.

✦ Use Case:

• E-commerce platforms: Examining how a platform will respond when its user base grows during a sale or the introduction of a new product.
• Procedures for data migration: Examining the system’s capacity to move substantial amounts of data between systems.

Also Read : Different Types of Software Testing: A Detailed Overview

How To Choose the Right Type of Performance Testing?

Choosing the right sort of performance test for the app depends on a number of criteria. It includes its goal, customer expectations, and the unique circumstances it may face. Here is how to make a strong decision.

1. Identify Your Goals

Begin by selecting the most important components of your application. Is it critical that your app stays reliable under high usage? Is it as such as an e-commerce website on Black Friday? Is it more vital that it can manage unexpected traffic surges? It can be ticketing systems during a large event. Understanding these goals will lead you to the appropriate exams.

For example, if you are concerned about user experience during high traffic, load testing or spike testing should be key objectives.

2. Consider Your Application Type

Analyze your present and prospective user base. If you think of considerable expansion, scalability testing is critical. It is to ensure that your application can manage the additional demand as your user base grows. If an app is data-heavy, volume testing is essential to guarantee that your databases can handle the load with no performance decline.

3. Assess Expected Traffic Patterns

Evaluate the hazards of system failure. Applications that must run continuously, such as financial services or video streaming platforms, might benefit from endurance testing to verify they can function properly over time. If a system breakdown while peak usage would prove disastrous, stress tests should be an important element of your testing approach to discover bottlenecks and avoid possible failures.

4. Budget and Resources

Customize the evaluation strategy to the exact circumstances that your application may experience. For example, if you are thinking of unexpected, considerable usage structures, spike testing is required. It is to determine how your system manages sudden increases in demand. If the performance of the software is crucial over a longer time, endurance tests assist you in discovering errors such as memory leakage. You can also identify decreases in performance that surface only after protracted use.

Various load testing types necessitate various tools. Make sure you are utilizing the appropriate ones for your requirements. The correct performance testing tool may improve the methodologies of testing & send accurate reports.

Performance testing is not a one-time process. Your testing strategy should change alongside your application. Revisit the results of your tests frequently to prove that they match the current state of your application and future goals. Scalability testing should be performed on a regular basis as your user base increases or when new features are added to avoid potential performance concerns.

You can ensure a smooth, dependable user interface even in the most demanding situations by carefully selecting the sorts of evaluations that are most appropriate for your application’s specific requirements and problems. This proactive strategy not only helps you prevent future hazards but also improves your app’s reputation and user happiness.

Best Practices for Effective Performance Testing

⇨ Set Clear Performance Benchmarks

• Regardless of the measurements or KPIs you employ, attempt to establish explicit, quantifiable performance objectives as early as possible. Without clear goals from the start, your testing will be unfocused.

⇨ Use Realistic Scenarios

• To obtain reliable findings, simulations should closely resemble real-world settings. You may do a capacity test using hardware that is smaller than the production size. However, production should not exceed three times the size of the largest test you did. With little hardware space, it is easy to overlook details.

⇨ Automate Where Possible

• Use automation wherever possible. AI can assist in evaluating performance data more effectively and identify possible problems quickly.

⇨ Monitor Continuously

• Constantly monitor the system’s performance before and after assessment to detect problems early. While testing, if you have a test that is at a critical point in a phase, run it twice. It’s simple to conduct a test once, draw a conclusion, and then realize that the findings don’t replicate.
• You may do a capacity test using hardware that is smaller than the production size. However, production should not exceed three times the size of the largest test you did. With little hardware space, it is easy to overlook details. Keep thorough records of test findings to monitor developments in performance over time.

Boost Your App Speed with Expert Performance Testing Now!

By covering the above content, you now understand that performance testing should be performed before the app launch. The following method is effective to ensure the system runs in the best condition. In modern software development, it’s a crucial step. By choosing the right types of performance testing and tools, you can ensure that your application matches all the performance benchmarks. If you want to deliver the highest quality satisfaction to the users, then talk with the performance testing company. Follow the best practices shared in the above-mentioned sections, along with expert guidance.