To identify performance bottlenecks and ensure that your product meets the market’s high standards, performance testing is essential.

In this article, we’ll explain what performance testing is, explore its different types, cover best practices for using it effectively, and look at the pros and cons of this approach to evaluating an application’s capabilities.

What is performance testing?

Performance testing is a type of software testing focused on evaluating the performance and scalability of a system or application. It helps identify and fix bottlenecks, measure how the system performs under different loads and conditions, and assess its ability to handle the expected number of users or transactions.

Performance testing answers an essential question: does the system meet the speed, responsiveness, and stability requirements under load to ensure a positive user experience? Typically, performance testing is conducted after functional testing is complete.

Purpose of performance testing

The following are the main goals and objectives of performance testing. 

1. Identifying system bottlenecks, which are specific areas within a system that hinder its overall performance. For instance, during load testing of a popular website, it was discovered that as traffic increased, server response time spiked significantly. Further analysis revealed that the system was generating the homepage from scratch for every request, involving multiple database queries. In this case, the bottleneck was the inefficient homepage generation process.
2. Verifying system compliance with the manufacturer’s specifications as well as industry standards and regulations.
3. Ensuring speed, stability, reliability, and scalability by detecting performance issues early in the development process. Addressing these problems upfront helps lower the costs associated with fixing performance issues later on.
4. Proactively resolving performance issues identified during testing to ensure the product meets user expectations and is prepared to handle unexpected situations.

Types of performance testing

Performance testing is an umbrella term that encompasses several types of testing. These include stress testing, spike testing, scalability testing, volume testing, soak testing, and endurance testing.

Stress Testing

Stress testing is a type of load testing that checks the stability and reliability of a system when it’s subjected to loads beyond its normal capacity. It helps identify potential issues that may arise under high or extreme load conditions. Stress testing focuses on the system's reliability, availability, and error handling under heavy load, rather than its behavior during typical usage.

For example, during load testing of a web service, experts simulate a significant increase in the number of concurrent users and transactions over a set period to evaluate the expected response times and uncover bottlenecks.

Stress testing is especially crucial for mission-critical software but is used across all types of applications. It helps development teams understand the scalability of workloads and shows how long it takes for a system to return to normal operation after an extreme event. Stress tests can be conducted either before or after the system is deployed.

Spike Testing

Spike testing is a subtype of stress testing that evaluates a system’s performance under sudden and extreme surges in load. Spike tests help determine whether a system can handle sharp, rapid increases in demand over a short period of time. This type of testing not only examines the maximum load the application can handle but also assesses its recovery time between spikes in activity.

Typically, spike tests are used to evaluate how an application behaves during drastic changes in traffic. They are often conducted before major events (such as Black Friday) when the system is likely to experience higher-than-usual traffic volumes.

Scalability Testing

Scalability testing is a type of non-functional testing that assesses the performance of a software application, system, network, or process in terms of its ability to scale up or down based on the number of user requests or other performance-related attributes.

This testing can be performed at the hardware, software, or database level. Scalability testing ensures that the software product can handle planned increases in user traffic, transaction frequency, and similar factors.

Volume Testing

Volume testing (also known as flood testing) is a type of software testing conducted to check how an application performs with a specific volume of data. This could involve testing with a large database or sizable data files exchanged between systems.

For example, during volume testing, a large amount of data is stored in the database, and the behavior of the entire system is observed. The goal is to assess the performance of the product with varying data volumes, understand how an increase in data affects the system, and identify the point where system stability starts to degrade.

Soak Testing

Soak testing, also known as endurance testing, is a type of software testing where the system is subjected to heavy loads over an extended period of time. It evaluates whether the system can handle a high volume of load for a prolonged duration, ranging from several hours or days to even a year.

Soak testing helps uncover potential risks associated with long-term use of the application, assists in capacity planning, and supports informed decisions about resource scaling. It also assesses the user experience under extended load conditions.

Soak testing is particularly crucial for systems that will be deployed in a production environment, as it helps identify issues that might not become apparent during shorter test periods.

How to perform performance testing

Since performance testing includes various types of testing, the process can vary significantly in each specific case. However, the following stages are generally relevant:

Define performance acceptance criteria, goals, and testing objectives

At this stage, it’s important to clarify what you want to achieve through the testing. Understanding the performance acceptance criteria is a critical part of the performance testing process. It helps define how well the application, website, or program should perform.

Performance acceptance criteria are the benchmarks that a system must meet to be considered successful. These can include metrics such as software or website loading speed, the number of users it can handle, or how it displays across different devices.

Set up the testing environment

In this stage, you need to prepare both test and production environments, ensuring all necessary devices, software, and tools are in place. The test environment is a combination of hardware and software used to simulate the behavior of the website or application in a live scenario. It includes operating systems, browsers, web servers, and databases.

Perform test planning

This stage involves writing various test scenarios based on expected user behavior and different situations. These scenarios should align with the performance metrics defined earlier.

Prepare your tools

By now, you've set clear testing goals and objectives and written the test scenarios. Based on this information, you need to properly configure the test environment, tools, and tracking mechanisms to monitor the test results.

Test

Create and execute the tests, carefully tracking all data gathered during the testing process.

Analyze and retest if needed

After running the initial tests, analyze the collected data and adjust the tests if necessary. Then, run them again to check if performance has improved or degraded. Repeat this process until you're satisfied with the results.

Performance testing metrics to monitor

Performance testing metrics are the indicators or parameters collected during the performance testing process. These metrics allow testing engineers to assess the success of the performance testing and identify critical areas in the software that need improvement.

Here are some of the key performance testing metrics:

• CPU usage: the percentage of CPU power used when processing requests.
• Memory usage: the amount of main memory (RAM) consumed during the processing of requests.
• Response time: the time between sending a request and receiving a response. The lower the response time, the better the performance of the website or application.
• Average page load time: the time it takes to fully load and display a web page in the browser. This metric is critical, as every second of delay increases the likelihood that a user will abandon the site, resulting in potential customer loss.
• Throughput: the measurement of the amount of data that can be transferred in a given period. Throughput helps evaluate how quickly a file or webpage can be loaded. Higher throughput means more data can be processed in less time.
• Average latency (wait time): the time a request spends in a queue before being processed.
• Error rate: the percentage of requests that result in errors compared to the total number of requests. This metric helps assess the reliability of the system under load.
• Concurrent users: the number of users or devices simultaneously interacting with the system. This metric is crucial for determining how well the system handles large volumes of traffic and whether it can maintain performance under heavy load.
• Requests per second (RPS): shows how many requests or tasks the system can process per second. This helps gauge the load your application or system can handle.
• Passed or failed transactions: the number of times a program can complete transactions from start to finish without errors.

To effectively track these metrics during performance testing, a range of monitoring tools and software solutions are used. These tools provide real-time dashboards that allow testers to observe how the system behaves under different load conditions and make data-driven adjustments to optimize performance. Regular tracking of these metrics ensures that performance issues are identified early, preventing larger problems after deployment.

Advantages of performance testing

Identifying bottlenecks. Performance testing helps identify bottlenecks in the system, such as low throughput or insufficient memory capacity. This allows developers to optimize the system and ensure its smooth operation.

Improving scalability. By determining the system's limits, performance testing ensures that it can handle potential or planned increases in the number of users or transactions.

Enhancing reliability and reducing risks. By uncovering potential issues that may arise under heavy load, performance testing enables developers to address them, thereby enhancing the system's reliability and stability and reducing the risks of system failure in production.

Cost reduction. Detecting and resolving issues during the testing phase is significantly cheaper for companies than addressing problems that arise in production.

Improving user experience. Identifying and fixing issues early on ensures that users interact with a more refined product, resulting in a positive experience. This can help increase customer satisfaction and loyalty.

Preparedness for unexpected scenarios. Performance testing provides insights into how the system behaves under various conditions, helping companies prepare for unforeseen situations, such as sudden traffic spikes.

Compliance with standards. Performance testing can assist companies in meeting regulatory and industry standards.

Ultimately, performance testing offers a deeper understanding of the system and its behavior in different situations, which enhances confidence in the product and ultimately ensures end-user satisfaction.

Challenges of performance testing

When deciding to implement performance testing, it's important to understand its drawbacks as well.

Resource intensity. Performance testing can require significant hardware and software resources, especially when simulating numerous users or transactions. This can make performance testing costly and labor-intensive.

Complexity. Like any complex technical process, performance testing demands specialized knowledge and experience. If a company lacks experts capable of writing intricate test scenarios or cases, successfully executing performance testing can be challenging.

Lack of real-world comparison. It’s important to recognize that even if testing is conducted in an environment close to reality, it remains a simulation. Accurately modeling real-world usage of your application and predicting how users will interact with the system — and whether it can handle the expected load — can be difficult.

Additionally, performance testing focuses on the system's performance under load and cannot uncover all types of issues or bugs. Therefore, it's essential to combine performance testing with other testing methods, such as functional testing, regression testing, and acceptance testing.

Performance testing is a crucial step

Performance testing is a critical tool in ensuring software quality, allowing developers and testers to assess the speed, stability, and scalability of a system under various loads. This method plays a key role in the modern development process by helping to identify bottlenecks, optimize resources, and enhance user experience.

Due to its multifaceted nature, which includes various types of tests, performance testing provides a comprehensive evaluation of the system. It is particularly valuable for preventing issues related to high loads and ensuring the system's readiness for unexpected usage scenarios.

Despite challenges such as resource intensity and implementation complexity, the benefits of performance testing far outweigh its drawbacks. It not only enhances reliability and reduces the risk of system failure but also helps lower long-term costs associated with fixing bugs. Ultimately, performance testing is an integral part of creating quality, scalable, and resilient software products that meet user expectations and business requirements.