In today’s market, load testing your software is considered the cornerstone of software performance evaluation. It’s the litmus test that determines whether your application can withstand the pressure of real-world usage. It often falls prey to misconceptions, particularly concerning concurrent users. However, misconceptions surrounding concurrent users in load testing often lead to flawed testing methodologies and inaccurate results. Today, we aim to shed light on the significance of understanding concurrent users’ impact in load testing.


What are Concurrent Users in Load Testing?

Concurrent users refer to the number of users accessing an application simultaneously. In load testing, simulating concurrent users involves mimicking the behavior of multiple users interacting with the application concurrently. This includes actions such as logging in, navigating through different pages, submitting forms, and accessing various features.

Concurrent users are like the number of users visiting your website and doing different things over a set period. Picture it as having users checking out your site at various times, some browsing products, others reading blogs, and some making purchases. They’re not all doing these things simultaneously, but they’re still counted as concurrent users. In performance testing, it’s like measuring how long your users hang out on your site.

Many developers mistakenly believe that replicating the exact number of current users during load testing is sufficient to evaluate an application’s performance. However, this approach oversimplifies the complexities of real-world usage scenarios. User interactions are dynamic, with varying levels of engagement, session durations, and requests per second. Each concurrent user generates requests to the system, mimicking real-world usage scenarios. Contrary to common belief, concurrent users don’t necessarily perform the same actions simultaneously. Instead, they collectively simulate a diverse range of user interactions with the application.


How Concurrent Users in Load Testing Works

When conducting load testing with realistic user scenarios, testers simulate various levels of concurrent users to gauge the application’s performance under varying loads. This process involves creating virtual users who emulate typical user behaviors such as browsing, searching, submitting forms, or making transactions. By introducing increasing numbers of concurrent users, testers can identify performance bottlenecks, scalability limits, and other issues that may impact the application’s responsiveness and user experience.

Understanding the impact of concurrent users in load testing is crucial for accurately assessing the application’s performance and scalability. By analyzing metrics such as response times, throughput, and error rates under different concurrent user loads, testers can identify potential issues and optimize the application’s performance accordingly.



Concurrent User Misconceptions in Load Testing

Rather than fixating on the number of concurrent users, testers should focus on creating realistic user scenarios. This involves considering factors such as user behavior, session durations, and the frequency of requests. By replicating authentic usage patterns, testers can obtain more meaningful insights into the application’s performance.

Several misconceptions about concurrent users in load testing exist, which can lead to confusion or inaccurate testing results. Here are some common misconceptions:

  • More Concurrent Users Always Mean Better Testing: There’s a misconception that conducting load tests with a higher number of concurrent users always leads to better testing outcomes. However, excessive concurrent users can overload the system and skew test results. It’s crucial to strike a balance and simulate realistic user loads to obtain meaningful insights into system performance. It’s important for you to determine a good estimate of concurrent users to use for your load tests rather than just the highest number of concurrent users.
  • Concurrent and Simultaneous Users are the Same: A common misconception is that both are the same thing. In reality, “concurrent users” represent the events that occur over a period of time whereas “simultaneous users” represent the events that occur at a point in time. Concurrent users may be active or inactive and may perform different activities. Simultaneous users must be active and perform the same activities at the same point in time.
  • Concurrent Users Equals Real Users: Another misconception is equating concurrent users in load testing with real users. While concurrent users simulate the load on the system, they are virtual users generated by the load testing tool and may not accurately reflect actual user behavior or traffic patterns.
  • Concurrent Users Must Reach Peak Traffic Levels: Some testers believe that load tests must simulate peak traffic levels by generating a high number of concurrent users. While peak traffic scenarios are essential to test system scalability, it’s equally important to assess performance under realistic user scenarios that may occur during regular usage patterns.


How to Determine Concurrent Users

When it’s time to conduct performance tests, paying attention to even the smallest details can make a big difference. Eliminating guesswork from key considerations, like figuring out concurrent users, not only saves time but also ensures more accurate test results.

For many teams, Google Analytics stands out as the primary tool for tracking website traffic and linking conversions to revenue. However, for those less acquainted with Google Analytics, pinpointing the precise number of concurrent users on a website can pose an initial challenge. Although the analytic report might show hundreds of visits per hour, the site could actually have just two concurrent visitors at a given moment. See the image below as an example.

Avwrage vs. Current Users


Determining the appropriate number of concurrent users for load testing is crucial for accurately assessing an application’s performance under realistic conditions. Here are some steps to help you determine concurrent users effectively before load testing:

  1. Understand User Behavior: Start by analyzing the expected behavior of your application’s users. Consider factors such as peak usage times, typical session durations, and the frequency of user interactions. This understanding will guide you in creating realistic user scenarios for load testing.
  2. Define User Scenarios: Based on your analysis of user behavior, define specific user scenarios that reflect real-world usage patterns. These scenarios should encompass actions such as logging in, browsing content, submitting forms, and accessing various features of the application.
  3. Identify Peak Load Scenarios: Identify peak load scenarios where the application is expected to experience the highest levels of concurrent user activity. This may coincide with specific events, promotions, or periods of high demand.
  4. Estimate Concurrent Users: Once you have defined user scenarios and identified peak load scenarios, estimate the number of concurrent users expected to be active during these periods. This can be based on historical data, user demographics, or projected growth.

Here are some steps to help you after you start load testing:

  1. Gradually Increase Load: Start load testing with a conservative number of concurrent users and gradually increase the load until you reach the desired level. This allows you to observe how the application responds to increasing levels of concurrency and identify performance bottlenecks.
  2. Monitor Performance Metrics: Throughout the load testing process, monitor key performance metrics such as response times, throughput, and error rates. This will help you gauge the application’s performance under different load conditions and identify any areas for optimization.
  3. Iterate and Refine: Use the insights gained from load testing to iterate and refine your user scenarios and concurrent user estimates. Continuously reassess and adjust your testing approach to ensure that it accurately reflects real-world usage patterns.

By following these steps, you can effectively determine the appropriate number of concurrent users for load testing and obtain meaningful insights into your application’s performance under varying load conditions. Load testing is an iterative process, and refining your approach over time will lead to more accurate results and a more robust application.


Understanding Concurrent User Impact

To understand the impact of concurrent users in load testing, testers must adopt a comprehensive approach. This involves analyzing both quantitative metrics (such as response times and throughput) and qualitative aspects (such as user behavior and feedback). By gaining insights into how the application behaves under varying load conditions, developers can make informed decisions to optimize performance and scalability.

In conclusion, breaking the misconception surrounding concurrent users in load testing is essential for ensuring the reliability and scalability of software applications. By prioritizing realistic user scenarios over raw numbers, testers can obtain more accurate performance evaluations and deliver a superior user experience. Load testing isn’t about simulating concurrent users; it’s about simulating real-world usage and preparing applications for the demands of the modern digital landscape. Check out our knowledge base article on concurrent users for more information. Get started load testing today with LoadView’s free trial and you’ll receive some free load tests from us!