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Dec 15, 2023 18 min read

Volodymyr Klymenko
CEO, Senior QA

How to do Performance Testing: Tips And Best Practices

This article is a comprehensive guide on performance testing, crucial for optimizing software applications. It details methodologies, such as using JMeter and Postman, and covers types of performance testing like load, stress, and scalability. Common mistakes like late testing and insufficient configuration are highlighted. It concludes with the importance of ongoing testing and the potential for automation, particularly in API testing with tools like Postman. The article serves as an essential resource for effective software performance testing.

How to do Performance Testing

In the rapidly evolving world of software development, understanding how to do performance testing is crucial for the success of any application. We explore various facets of how to do mobile app performance testing, reiterating its significance in the current tech era. The discussion extends to specific methodologies, such as how to do performance testing in JMeter, a popular tool for assessing application load and performance, and how to do performance testing using Postman for API testing. Through this article, readers will gain a holistic understanding of how to do performance testing across different platforms and applications, equipped with practical knowledge and tools to ensure their software performs at its best. 

What is Performance Testing? 

Performance testing is a crucial component of the software development process and is aimed at evaluating system performance. This process analyzes the software application's speed, scalability, and stability in various operating conditions.  

The primary purpose of performance testing is to provide visibility of potential application performance bottlenecks and to identify possible errors and failures. This process for performance testing ensures that the software meets the performance requirements before it is released into the live environment. 

Types of Performance Testing 

Performance testing takes many forms that aim to evaluate different aspects of the performance of a software or system. Here are some existing forms of performance testing: 


Load Testing: Load performance testing aims to determine how an application or system responds to many simultaneous requests. It simulates loads that exceed the average user load to identify potential performance and resource issues. You can learn more about this form of testing in our article


Stress Testing: Stress testing is a type of performance testing in software testing that evaluates system performance under extreme load conditions or resource constraints. The goal is to identify increased vulnerability and possible collapses under load. 


Spike Testing: Spike testing is stress testing aimed at evaluating software performance under a significant and rapid increase in workload that exceeds normal expectations. The program is subjected to intense and unexpected loads to reveal weak points in its performance for a short period. 


Soak Testing: Soak testing, also known as endurance testing, aims to simulate a gradual increase in end users over time to test the system's long-term stability. During such testing, the test engineer monitors critical performance metrics such as memory usage and checks for errors such as memory leaks. Throughput and response times are also analyzed after long-term use to determine whether these indicators correspond to their condition at the beginning of the test. 


Scalability Testing: This form of performance testing helps determine how the system scales when the volume of data or users increases. The goal is to ensure the system can maintain stable performance when resources or users increase. 


Capacity Testing: Capacity testing is similar to stress testing in that it tests the traffic load based on the number of users but differs in scope. Capacity testing verifies that an application or environment can handle the traffic it was designed to handle for a long time. 


Volume Testing: This testing determines how the system responds to processing a large amount of data. It helps identify possible problems with the amount of data, such as overflowing the database or increasing the processing time of requests. 

These performance testing types help testers ensure that the software or system operates with high performance and stability under various operating conditions. 

It is important to note that performance testing is non-functional because it does not test the software's functional aspects but focuses on its performance and resource consumption. 

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What is the Role of Performance Testing in Software Development? 

High-quality software is the key to success in today's market. The importance of application performance cannot be overstated. In this section, we will look at the role of performance testing in software development and its importance to success in this field. 

Improving the system's overall functioning: Performance testing helps identify weak points and improve efficiency and reliability. 

Assessing system scalability: It is important to determine how well the software can scale to meet the growing volume of users. This helps to plan future resources and ensure the system's stable operation even when the load increases.  

Failure recovery testing: Testing helps verify how quickly and efficiently a system can switch to duplicative components or recover from a failure, whether a hardware or software failure. This ensures minimal impact on users in case of problems. 

Monitoring stability and performance: The goal of testing is to see if the system remains stable and performant over a long period. This helps identify issues related to resource leaks or performance degradation over time.  

Architectural impact assessment: Performance testing can help identify whether changes to the system architecture, such as database optimization, distributed computing, or caching, should be made to improve performance.  

Resource usage assessment: Targeted testing includes resource usage analysis of the central processing unit (CPU), memory (RAM), and network traffic. This helps identify possible problems with the amount of resources and optimize their use. 

Code monitoring and profiling: Performance testing can include monitoring code execution to identify areas that consume a lot of resources or are the leading causes of failures. Profiling helps developers find optimization opportunities. 

Security testing under load: During performance testing, assessing the system's vulnerabilities and identifying potential security issues such as DDoS attacks or data leaks is critical. 

Performance testing plays a central role in software development. This process helps ensure that applications run optimally, increase their productivity, and ensure smooth operation, which are important success factors in today's software industry. 

Common Problems Revealed by Performance Testing 

While implementing software performance testing, QA faces various problems that can affect the efficiency and speed of the system. The most common of these include: 

Speed problems

  • Slow responses: Long waiting times for a system response can lead to user dissatisfaction and reduced productivity. 
  • Long loading times: Slow loading of an app or website can throw users off and cause them to lose interest in the product. 

Poor scalability

If software cannot scale efficiently, it can lead to delays, increased errors, and other undesirable behaviors. These issues are often caused by various systemic problems, including: 

  • Inefficient disk usage. 
  • Ineffective use of the central processing unit (CPU). 
  • Memory leaks. 
  • Limitations of the operating system. 
  • Problems with network configuration. 

Software configuration problems

  • Outdated settings: usage of old configurations and dependencies may lead to conflicts with updated environments (like a new version of a browser) 
  • Unconfigured settings: It is not uncommon for application settings to be set to an insufficient level, leading to poor performance during heavy workloads.  

Insufficient hardware resources

  • Physical memory limitations: Performance testing may reveal that the system does not have enough physical memory to run efficiently. 
  • Low CPU performance: If the CPU cannot handle tasks, it can significantly affect system performance. 
  • Network equipment limitations: Network equipment with low bandwidth can seriously limit the capabilities of a powerful server. 

Addressing these issues is critical to ensuring high productivity and user satisfaction when working with the software. Performance testing helps identify these problems and develop strategies before operating the system. 

Performance Testing Tools 

The table below lists performance testing tools that help you check how efficiently your software performs under load. Each tool has unique capabilities to help you find and solve performance issues. Read a brief description of each tool to choose the most appropriate one for your testing. 

Performance testing tool 


Akamai CloudTest 

  • Actively tests the performance and functionality of mobile and web applications. 
  • Simulates millions of concurrent users for load testing.
  • Provides customizable dashboards.
  • Conducts stress tests on cloud platforms.


  • Simulates test cases and conducts performance testing. 
  • Integrates with open-source tools and APIs. 
  • Tests mobile and web apps. 
  • Provides real-time reporting and analytics. 


  • Helps testers conduct performance testing to ensure stable and efficient software performance under various conditions.
  • Generates load tests for web services and application services.  
  • Provides plugins for flexible load testing.  
  • Supports graphs, thread groups, timers, functions, and logic controllers.  
  • Offers an integrated development environment for test recording. 


  • Tests and measures performance under load.  
  • Simulates thousands of users and records load tests.  
  • Generates messages between application components and user actions.  
  • Uses cloud resources. 


  • Specializes in performance testing of web and mobile applications.  
  • Monitors web servers, database servers, and applications.  
  • Simulates the behavior of millions of users.


  • Allows to execute and manage multiple API requests.  
  • Helps run sets of requests repeatedly with Collection Runner for basic load testing.  
  • Tracks API performance and response times.  
  • Scripts automated performance tests.  
  • Integrates with other tools for enhanced testing capabilities. 
These tools help testers conduct performance testing to ensure stable and efficient software performance under various conditions. 

Performance Testing Steps 

Step 1: Defining the Test Environment 

Defining the test environment is the first and pivotal stage in performance testing. The test environment, also known as the test bench, must meet the performance characteristics that are intended to be tested. The main aspects to consider are:   

  • Hardware: Hardware that matches the product architecture and considers possible loads is selected. It can be physical or virtual hardware. 
  • Software: The operating system, databases, server applications, and other components used in the real environment are configured.  
  • Network: Configure network parameters to match the real environment, including speed, latency, and bandwidth. 
  • Tools: Selection tools for monitoring, data collection, and performance analysis. 

Step 2: Determination of Performance Indicators 

Metrics are fundamental in ensuring the quality and effectiveness of performance testing. Two key terms to consider: 

  • Measurement is data collection during testing, such as the time it takes to respond to a request. Measurement acts as the primary means of obtaining objective information. 
  • Metrics are calculations used to determine the quality of an application based on measurements. For example, average response time is defined as the total response time divided by the number of requests. 

Measurements and metrics are defined by taking into account the main aspects of performance. There are different methods of measuring speed, scalability, and stability. However, in practice, only some stages of performance testing use all possible measurements. At this stage, testers define specific indicators that will be measured during testing. Key indicators include: 

  1. Response time: This is the total time from sending a request to receiving a response. 
  2. Wait time: The average latency indicates how long it takes to receive the first byte after sending a request.   
  3. Average load time: Determines how long it takes to deliver each request and is the primary quality indicator from the user's perspective.  
  4. Peak response time: Measures the longest time it takes to complete a request, which can indicate anomalies. 
  5. Error rate: This metric indicates the percentage of requests with errors compared to all requests. 
  6. Concurrent users: Determines the number of active users at any given time, known as the load size. 
  7. Requests per second: This shows how many requests are processed in one second. 
  8. Transactions Passed/Failed: Measures the total number of successful or failed requests. 
  9. Throughput: Determines the amount of bandwidth used during the test. 
  10. CPU and memory utilization: Indicators characterizing the load on the equipment.  

These metrics are essential for measuring performance and ensuring system efficiency during use. They allow you to identify problems and optimize the product before its release. 

Step 3: Planning and Designing Performance Tests  

At this stage, performance test scenarios that consider the system's real use are developed. Scenarios can be targeted at users, operations, and workloads. This includes:   

  • Test Data: Setting the input data for scenarios as realistic as possible. 
  • Targets: Defining specific metrics that should be achieved during testing. 

For web applications, performance testing involves simulating various user interactions and loads to assess the application's responsiveness, stability, and scalability. It's crucial to create test scenarios that mirror real-world usage to ensure the web application performs optimally under diverse conditions. 

When conducting a performance test on a PC, it's important to measure the system's response time, processing speed, and resource utilization under different conditions. Utilize specialized software tools to simulate a range of operations and workloads, ensuring the PC can handle tasks efficiently in various scenarios. 

Step 4: Setting up the Test Environment 

At this stage, all necessary components of the test environment are prepared. This includes installing the necessary software, configuring the network and hardware, and preparing monitoring tools. 

To learn how to do performance testing for a web application, begin by establishing performance criteria like response time and throughput, and then use tools such as Apache JMeter to simulate various user loads and assess the application's behavior under stress.  

Understanding how to do a performance test on a PC involves selecting the right benchmarking software, like 3DMark or Cinebench, to evaluate your computer's processing power, graphics capabilities, and overall speed, ensuring it meets the required performance standards for your specific needs. 

Step 5: Development of Test Scenarios 

At this stage, tests are developed according to the scenarios created in the planning and designing stage. Each test must be documented in detail and consider real operating conditions. 

Step 6: Conducting Performance Tests 

Performance tests are conducted during this phase, and system monitoring is performed simultaneously. Performance data is collected and analyzed on the fly to identify problems that may occur under load. 

The question of how to do performance testing for a web application typically involves creating a series of tests that progressively increase user load and interactions. It is pivotal to use specialized tools to evaluate how well the application maintains its performance under various stress conditions.  

When addressing how to do a performance test on a PC, the process includes systematically running a suite of tests using specific software to assess different aspects of the PC's performance, such as CPU efficiency, memory usage, and graphics processing, to ensure it operates effectively under different operational loads. 

Step 7: Analyze, Report and Retest 

After the tests are completed, a detailed analysis of the results is carried out. A report is generated with performance information, including issues identified and recommendations for improvement. Based on this analysis, changes can be made to the system. After changes are made, retesting may be conducted to verify the effectiveness of the changes. 

Performance testing is an integral part of the software development process, which allows you to ensure that software operates effectively in actual operating conditions. Detailed planning, setting up the environment, and analyzing the results are imperative steps that help identify and correct potential problems before releasing the product. 

Performance Testing Best Practices 

Performance testing is recognized as one of the critical components of success in software development. We have prepared for you a list of tips based on our own experience: 

Early Testing and Regular Inspections 

The most critical piece of performance testing advice is to test early and review regularly. Testing only in the final stages of development can lead to discovering severe problems that will take time to fix. Performance testing should be completed on time until the product is released. 

Testing of Individual Blocks or Modules 

Performance testing does not necessarily have to be done only on completed products. It is important to understand that you can conduct separate tests for individual blocks or modules, even if the product is not yet ready. 

Multiple Performance Tests 

This will help establish the results' consistency and determine the performance indicators' average values.  

Involvement of the Team in the Process 

Involving developers and other IT professionals in creating a performance test environment helps ensure that the test conditions are realistic.  

Development of Realistic Models 

To achieve the most accurate results, it is worth developing realistic models that consider the activity of real users. 

Analysis of Extreme Values  

When analyzing test results, you should consider average values, outliers, and extreme measurements that can reveal possible anomalies. 

Reporting and Change Accounting 

Preparing reports that share performance test results and include any system and software changes is an important part of the performance testing process. 

These techniques help ensure effective performance testing and improve software quality before release. Testers must follow these practices to ensure optimal software performance and user satisfaction. 

Common Performance Testing Mistakes to Avoid  

Performance testing is an integral part of the software development process, but several common mistakes can undermine the reliability of the results. Here are the mistakes to avoid: 

  1. Late Testing: Testing done late in development can be unproductive because it is difficult to fix the discovered problems. It's important to start testing as early as possible to identify and fix problems immediately.  
  2. No Developers Involvement: Performance testing requires collaboration between developers and testers. Including developers helps ensure that essential aspects of the software code are considered in the tests. It is better to involve developers from the beginning for optimal results. 
  3. Absence of Quality Control System: Having a quality control system akin to the production system is crucial for effective overall testing and specific types of testing as a component of this process. Such a system facilitates easier tracking of performance changes and quicker identification of issues that emerge during testing. 
  4. Insufficiently Configured Testing Software: Only properly configured testing software can guarantee correct results. Settings such as resource throttling and resource monitoring must be properly configured for test accuracy. 
  5. Lack of a Troubleshooting Plan: Performance testing can be worthwhile with a clear troubleshooting plan. Once problems are identified, it is crucial to have a plan of action to correct them and improve performance. 

Avoiding these common mistakes will help ensure effective performance testing and improve software quality before release. 


In this article, you became familiar with the features of performance testing, understood its role in the software development process, learned how to conduct it correctly, examined the nuances of each stage, and received a list of tools with a detailed description of their functionality. We hope this knowledge will prove helpful to you and that you can effectively implement it in practice. At Luxe Quality, we are ready to offer high-quality performance testing services to ensure your software meets the highest standards of efficiency and reliability. Our expertise and tools are at your disposal to help you achieve optimal performance in your software projects. 

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What are the important metrics used in performance testing?

Key metrics include response time (how long the system processes a request), throughput (the number of requests the system can process per unit of time), and CPU load. Other important metrics include error rate, average load, and peak response time. 

How do I determine how much load my system can handle?

Conducting tests with a gradual load increase is necessary until the system shows signs of overload. It is important to consider the volume of requests and the distribution of users, their activity, and other factors. 

Is it possible to automate performance testing, and how is it done?

Yes, performance testing can be automated. This is achieved with test automation tools that create scripts and track performance metrics automatically. 

Why should performance testing be an ongoing process and not a one-time event?

Performance testing should be ongoing because developers are constantly changing the system. New features, updates, and changes can affect performance, and detecting and adjusting them is vital. It’s a non-functional analog of functional regression testing. 

How to do performance API testing using Postman?

To perform performance API testing using Postman: 
1. Create API requests in Postman that you want to test for performance. 
2. Utilize Postman Collections and Environments to organize your requests. 
3. Implement test scripts to simulate various user scenarios and loads. 
4. Use the Postman Collection Runner or Newman (command-line tool) to execute multiple requests concurrently, generating performance data. 
5. Analyze the performance metrics, such as response times and throughput, to assess your API's performance under different conditions. 
This approach allows you to automate efficiently and scale API performance testing using Postman.