Updated Nov 08, 2024 16 min read
How to do Load Testing? [A FULL GUIDE]
Load testing is non-functional software testing that evaluates a software application's performance under a specific load, such as many simultaneous requests. This process involves analyzing and evaluating how the application behaves under the conditions of simultaneous access by many users. Some consider stress testing a separate type, while others consider it part of load testing. This article will also show the difference between load testing and stress testing.
What is load testing?
Load testing is non-functional software testing that evaluates a software application's performance under a specific load, such as many simultaneous requests. This process involves analyzing and evaluating how the application behaves under the conditions of simultaneous access by many users. Some consider stress testing a separate type, while others consider it part of load testing. This article will also show the difference between load testing and stress testing.
The primary purpose of load testing is to identify possible weak points in performance and guarantee the software application's stability and flawless performance before its production release. This type of testing is one of the subcategories of performance testing. A load test measures systems' performance under a predicted load. For this, scenarios are created where virtual users perform transactions during a specific period.
Why do you need load testing?
Load testing plays an indispensable role in ensuring the reliability and performance of the system, which is why the question of how to do load testing arises more and more often. This type of testing detects potential bottlenecks in a system before they can affect its functioning in real-world environments.
Key benefits of load testing
- Predicting weaknesses: Stress testing (A type of testing that evaluates the system's resilience under severe or extreme conditions, such as many requests, excessive load, or data volume. It helps identify system weaknesses in scenarios of intense user stress, even before they are discovered in the work environment, reducing the risk of system failures or degraded performance
- Effective performance management: The results of load tests provide additional insights into effective performance management and developing strategies for optimizing the production environment, even during heavy usage.
- The realism of scenarios: During load testing, you should use real-life user scenarios considering different aspects of the system.
- Geographic diversity: You can test how the system responds to loads from different geographical regions, which helps ensure its reliability and availability for users worldwide.
- Constant monitoring: With regular load tests, you make certain that your system is always ready to work under real load conditions.
Avoiding unsatisfactory performance and reducing the risk of production downtime is the primary goal of load testing. With the digitization of business, the importance of knowledge of how to do load testing is increasing. Businesses and users trust applications to perform critical tasks, so ensuring the system can handle real-world workloads is essential.
As the most common type of performance testing, load testing puts software applications and systems under normal user payload. Its purpose is to check whether they function effectively under normal conditions. Compared to its "brother" - stress testing, which, on the contrary, overloads systems to failure, load testing confirms that a function, program, or system will cope with its operational purpose.
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When should you do the load testing?
While load testing should be run regularly as a proactive measure, it becomes particularly crucial before high-traffic events or following modifications to your application architecture, system dependencies, or code algorithms. You can also learn how to do performance testing to optimize your software's speed and efficiency.
When to run load tests?
- High-traffic events: Load testing is imperative before significant traffic surges, such as during product launches, flash sales, and ticket sales. This preventive measure ensures that your service remains stable and available during these critical moments.
- System changes: Any substantial modifications to your application's architecture, system dependencies, or code algorithms warrant load testing. Even seemingly minor alterations can substantially impact performance, making load tests an important tool to measure and comprehend these effects.
- Regular testing for the unexpected: Regular load tests are indispensable for handling unexpected traffic spikes beyond scheduled high-traffic events. These unforeseen increases can result from PR appearances, viral social media posts, or celebrity endorsements.
- Early load testing: Commencing the load testing process is essential due to its iterative nature. Planning and execution require meticulous preparation, as identifying and addressing performance bottlenecks may require multiple testing and optimization rounds.
In summary, running load tests is irreplaceable at three critical junctures: before high-traffic events, following application changes, and as part of regular performance testing. Adequate planning and early initiation ensure a comprehensive testing process, enabling you to optimize your application's performance and deliver a seamless user experience.
Load Testing vs. Stress Testing
As for stress testing, its job is to push requirements beyond the limits, provoking failures and helping to identify risks in the event of failures. In this way, you can optimize your application settings for better stability. Stress testing prepares for unexpected situations and helps determine how the system works at the edge of performance.
The main differences can be explained in more detail below:
Aspects | Load testing | Stress testing |
---|---|---|
The main purpose | Detection of boot locks in the system under various loads and observation of the system's reaction when the load is gradually increased | Determining the system's failure limit to identify the maximum load after which it breaks down |
Load limit | Setting an upper system limit, usually through an application SLA, and evaluating the system's ability to handle a heavy load | Assessment of system behavior under extreme loads and recovery after failures |
The main task | Simulation of maximum load on the web application | Find out the limit of the peak user load up to which the system will work without failure. |
Tested parameters | Analysis of peak performance, number of servers, and response time | Evaluation of stability, response time, time of restoration after failure, etc |
So, load testing reveals the system's limitations in normal conditions, while stress testing determines the endurance limit under extreme loads. Both types of testing are essential to ensure stable and productive system operation in various conditions.
Strategies of load testing
There are many options for carrying out load testing. We have prepared for you a list of the main ones:
Manual Load Testing: While manual load testing is a strategy for running load tests, it often needs more repeatability, fails to provide measurable stress levels on an application, and proves challenging to coordinate effectively.
In-House Developed Load Testing Tools: Organizations recognizing the significance of load testing may create tools for executing load tests. This approach offers customization and control tailored to specific requirements.
Open-Source Load Testing Tools: Numerous open-source load testing tools are available without cost. While they might possess a different level of sophistication than their paid counterparts, they are an economical option, especially for those with budget constraints.
Enterprise-Class Load Testing Tools: These tools typically include capture/playback capabilities and support many protocols. They excel in simulating a substantial volume of users, making them suitable for testing high-performance scenarios and complex systems.
It's essential to choose the right load-testing approach based on the project's needs, available resources, and desired level of accuracy in reproducing real-world scenarios (you can learn about the importance of software testing for marketplace platforms).
How to do a load testing: step-by-step guide
Step 1: Start
When we start any multi-step process, we should clearly outline and analyze the main steps and define the purpose and goal of the process. The implementation of load testing is no exception. Before starting the work itself, you should perform the following actions:
- Gather requirements: Identify the key functionalities to test and focus on what shapes the user experience.
- Describe user steps: Describe user interaction with the program. Use APM monitoring for additional data.
- Establish a baseline: Run tests to determine a stable performance baseline. Deviation from this indicator indicates possible problems.
- Automate and integrate: Prioritize load testing in your CI/CD process. Integrate it with existing tools.
These steps will provide a solid foundation to start load testing your application successfully.
Step 2: Working with acceptance criteria
Acceptance criteria are the essential conditions that load test results must meet to be accepted. Competently defined acceptance criteria help to avoid unexpected cases in natural conditions and guarantee the satisfaction of all interested parties and users with the obtained results.
These criteria should be determined before tests are created based on the expected and required results from the program. Some of the more common and important criteria include:
- Reaction time
- Percentage of errors
- Using the processor
- Memory usage
- Using the disk
Correctly defined and used in tests acceptance criteria will help ensure the quality and reliability of load testing, contributing to a positive user experience and confidence in the operation of the software.
Step 3: Prepare the data carefully
For successful load testing, it is pivotal to carefully select the data that will be used during the test. Since the goal of stress testing is to simulate the actual workload of the application, the amount and quality of the data have a decisive influence on the realism of the test scenario.
It is essential to consider that it is not enough to increase the volume of data - its quality is also of great importance. The data must be representative and reflect users' program use scenarios. This will allow you to more accurately reproduce real conditions and identify potential problems that may arise under an actual load.
Thus, adequately selected data for load testing will create a more accurate, realistic, and practical test scenario, allowing timely detection and resolution of potential problems before they occur in real production conditions.
Step 4: Creating test cases
Generating test cases plays a crucial role in determining system performance and reliability. This critical stage allows you to establish the optimal level of functioning and collect information for future comparative analysis. It makes sense to focus on the app's critical features that users use most – for example, in e-commerce, this could be the buy button.
When creating test cases, consider these significant factors:
- Expected load: Determine the expected load that the program must handle. This will allow you to set the optimal amount of workload.
- Conformance: Ensure the application responds to each request as expected. Ensure that all functions meet the expected performance.
- Desired response time: Determine the total time required to receive a response to the request. This will help to evaluate the performance and response time of the system.
Specific test cases allow you to evaluate the application's response to different usage conditions, including the performance of important features that users use the most.
Step 5: Test execution
During load testing, the test performs specific actions to monitor results and verify the viability of the test environment. These steps are essential to successfully performing this type of testing, so they will help ensure the accuracy of the results.
Additionally, check the server’s engine’s functionality during load testing. Indicators of processor usage should remain at levels no higher than 75% and the amount of RAM - at levels of 70%. If these thresholds are exceeded, consideration should be given to optimizing the system by increasing server capacity.
Choosing the Right Tools
A pivotal decision in load testing lies in selecting the most suitable software to achieve accurate and comprehensive performance assessments. While running load tests on your in-house infrastructure is an option, numerous enterprises opt for third-party performance testing services to ensure a robust evaluation, which often includes guidance on how to do load testing for a website.
A spectrum of load-testing applications is available, catering to diverse testing needs and preferences. These tools can be broadly categorized into open-source options and software as a Service (SaaS) offerings, each possessing distinct advantages.
Open-Source Load Testing Tools
- JMeter: A Java-based powerhouse tailored for load testing, enabling meticulous examination of web applications' response times. Renowned for its versatility and popularity, JMeter remains a go-to choice for many testers.
- Gatling: A dynamic load testing solution for continuous load testing. Gatling's strength lies in its seamless integration with development pipelines. Executed through Scala code, Gatling tests return results in HTML format. Additionally, Gatling is available as a SaaS product via Gatling Enterprise, further increasing its potential.
- The Grinder: A Java-based load testing framework designed to organize distributed tests using a network of load generators. Compatible with systems housing a Java API, The Grinder provides a flexible approach to load testing.
- Locust: Based on Python, Locust presents a distributed load testing paradigm capable of filling the systems with millions of concurrent users. Its user-friendly interface allows testers to create concise dashboards and comprehensible test reports.
SaaS Load Testing Tools
- k6: An extension of the open-source k6 tool, k6 Cloud opens a new era of load testing. Recording user journeys on a browser allows the creation of test scripts. Testing is enriched by the ability to test from various geographic locations and simulate up to 1 million concurrent virtual users. Geared toward developers, k6 Cloud also delivers performance monitoring and an intuitive user interface.
- LoadNinja: This tool employs real browsers for load testing, including guidance on how to do load testing for a web-based application. The web-based approach authentically replicates high-traffic scenarios. The streamlined operation allows scriptless tests based on browser recordings, supported by analytical tools for dissecting performance outcomes.
- BlazeMeter: Purpose-built for Apache JMeter, BlazeMeter emerges as a robust contender. Streamlining test configuration facilitates rapid setup and execution of tests with up to 1 million concurrent users. Furthermore, it pioneers mobile testing simulations using actual devices alongside multi-geo location testing. While offering free tests with up to 50 concurrent users, it scales to accommodate larger loads for those seeking comprehensive evaluations.
- LoadRunner: A complex solution, LoadRunner targets comprehensive performance analysis of web applications, Enterprise Resource Planning (ERP) software, and legacy systems. Its distinct attribute lies in preemptively identifying bottlenecks before application release, allowing for optimizing performance ahead of deployment. Propelled by a patented auto-correlation engine, LoadRunner is an expert at detecting system, end-user, and code-level bottlenecks.
The diverse range of open-source and SaaS offerings enables you to ascertain performance resilience and deliver a flawless user experience.
Best Practices for Effective Load Testing
Do you find load testing difficult? Our specialists have prepared some tips for making your testing process easier.
Creating Realistic Scenarios
Put yourself in the user's shoes. What matters most to your users? Which aspects of your application are crucial for them? Do they access it from different devices and browsers? Realistic load-testing scenarios allow you to simulate your application's performance in real-world conditions with genuine users. Since user behavior can be unpredictable, introduce randomness and variation into your tests to simulate real-world scenarios accurately. Vary devices and browsers to ensure your application is well-prepared for deployment.
Testing Early and Frequently
While performance testing often takes place in isolation after development is complete, recent years have shown that increasing feedback throughout the software development lifecycle is precious in rapidly identifying and rectifying issues. Prioritize integrating performance testing, especially load testing, into your agile methodologies, continuous integration processes, and automation practices.
Using Real-Life Data
For authentic benchmarks and scenarios, leverage existing data. Reuse information from your monitoring tools to define what 'realistic' means in your specific context. Monitoring tools often provide proactive and reactive insights, enabling you to integrate synthetic and real user data into your load-testing scenarios. This encompasses user-generated data such as browsers, devices, user pathways, drop-off points, system-oriented data like DOM load, time to the first byte, and more.
Analyzing Test Data to Identify Underlying Issues
Once load tests are executed, the initial step is to pinpoint any problematic areas and develop strategies for enhancing those components' performance. This involves correlating performance bottlenecks with code to detect the root cause. Traditional testing tools may present challenges as test results must be translated into metrics that can be shared with the development team for deeper code analysis. However, with LoadNinja, this hurdle is eliminated, as its browser-based metrics enable real-time inspection and debugging of load test results (you can explore the benefits of cloud performance testing for scalable and reliable software performance).
Conclusion
So, in this article, you have learned a lot of things about the implementation of load testing, namely why this type of testing is implemented and what its advantages are, how to do load testing step-by-step, the main differences between stress testing and load testing, the main strategies and a list of the best tools, and of course the most valuable — the advice of our specialists to optimize this process. We hope that you will be able to successfully apply the acquired knowledge in practice. Learn more about our successful collaboration with QPilot. We're happy to share our experiences and demonstrate how our partnership has led to successful outcomes for our clients. Don't hesitate to reach out to us today. We're here to assist you and ensure the success of your project.
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Load testing is a type of performance testing that assesses how a system behaves under an expected load. It helps in determining a system's capacity and ensuring that it can handle the anticipated volume of users or transactions.
While both are subsets of performance testing, load testing evaluates how a system behaves under expected conditions, whereas stress testing assesses its behavior under extreme conditions or when pushed beyond its limits.
Some popular tools include Apache JMeter, LoadRunner, Gatling, and Locust, among others. The choice of tool often depends on the system's requirements and the tester's familiarity.
It's a good practice to load test after major changes to your application or infrastructure, before significant product launches, or at regular intervals to ensure continuous system optimization.
Some essential metrics include response times, throughput, error rates, server health metrics, and resource utilization (like CPU and memory usage).