Load Testing


In the process of software development whether agile or waterfall, the software goes through several tests to ensure its quality. But when the product goes live to its users, they not only expect the right functionality but also fast processing, quick responses and fewer failures when several users are using it concurrently. The testing which verifies the performance of the product under stipulated workload is known as Load Testing. It is the most frequently used performance testing type.

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What is Load Testing

Load testing is a type of performance testing which imposes workload on the product under a valid range and observes its performance parameters. It is done by simulating the expected user load on the product. This testing is often more suitable for a multi-user system having a client-server model. However, other software systems can also benefit from it.

Why Load Testing

We can test an application wisely using various testing available. But still, we cannot predict the behavior of the system when multiple users are using crucial functionalities of it. The only way to verify the performance before release is to do the load testing.

  • All the testing like unit, integration or system tests the system from a functional point of view with one user at a time. But load testing verifies the system realistically in a multi-user business environment.
  • It establishes the normal operational workload limits and breaking points of the application.
  • Load testing helps identify performance issues pertaining to the stability and robustness of the product.
  • It helps to avoid issues like downtime, failures, slow response before they happen in production. Thus, it helps in preventing revenue loss.

Load Testing use cases

  • When a new shopping app with launching discounts comes live, there can be a huge rush of buyers. The app should be able to handle these many users from the start. Here, load testing can be a lifesaver.
  • In the train booking system, when an emergency booking for the immediate tickets starts, there can be thousands of users booking the tickets.
  • During office commute time, there is a huge increase in the number of users of the music app. Load testing helps to deliver optimum performance during the demand surge.

How to do the load testing

At the gist, load testing is the process of subjecting the product to virtual user load and record its performance in terms of response time, throughput and scalability.

  • Requirement analysis: This phase requires gathering information about the performance requirements in terms of response time, scalability, stability, and throughput. One can identify the crucial area of the product and list out the performance expectations for that.
  • Planning: In this step, the team finalizes test schedule and budget, resources, tools and test scenario to cover.
  • Tool Selection: Load testing is typically done through the tool. The tool records user actions and generates the test scripts. Then these test scripts simulate multiple users working on the application. The most appropriate tool suitable for the project should be chosen.
  • Test Execution: Test scripts are executed while recording the results. Compare these results with the performance benchmarks set for the product and register any deviations. These deviations are the input for further investigation and fixing.
  • Performance tuning: After identifying the performance problems the next step is to fix the issue with code changes or provide workaround or configuration changes. This is the goal of the load test to remove the bottlenecks, identify and fix the resource utilization and hardware issues. Now an improved product all set to work in a real business environment providing optimum performance is ready.

Metrics for load testing

Response time

Total time elapsed between the request is sent and getting the response.

Average Load time

The average time to load the application.

Wait time

This represents the total time it takes to receive the first byte after sending the request.


Throughput shows the number of kilobytes used per second.

Transactions passed/failed

The total number of successful and unsuccessful transactions.

CPU utilization

This shows the time CPU takes to process the requests.

Load testing best practices

  • Real user scenarios simulation: It is important that the test scenario behaves like the real user using the system.
  • Frequent testing from the start: In the agile model, the small working part of the product is ready at the end of every sprint. Like any other testing, load testing should also be done.
  • Realistic Benchmarks: Setting too high benchmarks is not going to help. It is important to understand the application and then set the approachable benchmarks.
  • Production environment simulation: Not only the user behavior but also the load testing environment should be the copy of a real-life production environment for the testing to be effective. The whole idea of the load test is to simulate the workload which is similar to an actual business environment.
  • Test result analysis: It is important to dig deeper into test results and find out the underlying performance issues and bottlenecks. An appropriate amount of time should be allocated for this activity otherwise the whole purpose of testing is defied.

Advantages of Load Testing

There are numerous advantages of load testing like detection of performance bottlenecks before the product goes to production, improvement in scalability, reduction of system downtime, improved customer satisfaction, and reduced failure costs. Have a look at the below list:

  • Stability of the product: Load testing helps ensure that the system will provide stable performance during user loads.
  • Identification of performance bottlenecks: Load testing can effectively locate bottlenecks due to faulty code, improper design or configuration issues way before the product release.
  • Enhance System scalability: It helps to determine the system’s operating capacity and judge the performance when the users demand to scale up.
  • Better users satisfaction & revenue: With better performance, comes better user satisfaction. Thereby improving business and revenue.
  • Lower system downtime: It uncovers failure and downtime issues which may occur when there is heavy user traffic and allows fixing them upfront.

Challenges of load testing

  • Load testing is an expensive process involving the cost of tools and resources with the right skills. It requires coding and scripting skills from load testers.
  • The projects with tight schedules impose difficulty in implementation of load testing.
  • Although it simulates the real user workload pattern, the production business environment can be much more complex than this and product can still run into performance issues.

Tools for load testing

Load testing is typically done through the commercially available load testing tool. The selection of tool depends on various criteria like types of test scenarios, cost of the tool, skill set of the team, resources available and learning curve of the tool. Some of the most common tools for load testing are:

  • LoadRunner: LoadRunner from HP is a front runner tool for load testing suitable for huge test suites. It can simulate a large number of virtual users for load testing.
  • Apache JMeter: It is an open source purely Java application for load testing. It can test both static and dynamic resources and web applications. Also, it can simulate lots of load on web servers, group of servers, network, and objects for the load testing.
  • BlazeMeter: It is a powerful tool which can simulate millions of virtual users. Moreover, it is a commercial self-service load testing platform compatible with Jmeterand many other automation testing frameworks.
  • Load Test: This tool allows the testers to configure and tweak requests to simulate real-working environment loads.
  • WebLOAD: WebLOAD from RadView enables its users to establish sound load testing processes. It can help with the load testing of web and mobile applications.


Load testing tests system with the expected range of workload to determine its performance. Invariably, it can identify the performance issues and bottlenecks before the product goes into production. Thus, fixing the problems in the product from load testing makes the system more stable and robust for future real-life usage. Although it requires skilled testers to perform it but skipping it can cause huge revenue losses.



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