Load Testing Types and Simulations

Last Updated: May 17, 2024

Why Load Testing and Performance Testing Is Important

In today’s fast-paced digital world, where online presence is paramount for businesses, ensuring the performance and reliability of websites and web applications is non-negotiable. Inefficient web pages, whether slow to load or unresponsive, directly impact financial revenue. It’s crucial to conduct performance tests with appropriate load simulations to avoid potential disasters. When not executed correctly, frustrated users are likely to abandon tasks and seek alternative solutions, even if the issue is later resolved. This loss of engagement not only affects revenue but also damages consumer confidence and brand integrity, which are arguably more detrimental to the business. Delayed resolution worsens the challenge of rebuilding trust with consumers and prolongs the realization of returns on investments in products, teams, and organizations. Therefore, performance testing and monitoring have become indispensable components of software and application development.

Load simulation performance tests play a pivotal role in this process, enabling organizations to gauge their systems’ scalability and responsiveness under various conditions. Among the plethora of load simulation methods available, performance testing platforms provide a broad range of load simulation methods such as HTTP/S, headless, and real browser-based testing. In this article, we will outline the main aspects of each, followed by a comparison matrix that you can use for choosing an appropriate simulation approach.

Different Types of Load and Performance Tests

Load Testing: Load testing involves subjecting a system to anticipated loads to evaluate its response. The primary objective is to determine how the system behaves under normal and peak load conditions. By gradually increasing the load, testers can identify performance bottlenecks, such as slow response times or resource limitations.

Stress Testing: Stress testing goes beyond load testing by pushing the system to its limits and beyond. The goal is to identify the breaking point or threshold at which the system fails. Testers apply exceptionally high loads or unexpected scenarios to observe how the system handles extreme conditions. Stress testing helps uncover vulnerabilities, weaknesses, and potential failure points under immense pressure.

Soak Testing: Soak testing, also known as endurance testing, assesses the system’s stability over an extended period under a sustained load. Unlike other tests that focus on immediate performance metrics, soak testing evaluates long-term performance, resource leakage, and memory issues. This type of test is particularly crucial for mission-critical systems, ensuring they can maintain optimal performance over prolonged durations without degradation.

Spike Testing: Spike testing evaluates how the system responds to sudden spikes or fluctuations in traffic volume. It involves rapidly increasing and decreasing the load to simulate real-world scenarios like flash sales or viral content. Spike testing helps determine if the system can scale dynamically to accommodate sudden surges in traffic without crashing or experiencing downtime.

Volume Testing: Volume testing assesses the system’s performance under a significant volume of data. It focuses on handling large datasets, transactions, or user interactions without compromising performance or stability. By analyzing how the system manages data storage, retrieval, and processing, volume testing ensures scalability and efficiency as data volumes grow.

Concurrency Testing: Concurrency testing evaluates how the system handles multiple simultaneous users or transactions. It assesses concurrency control mechanisms, database locking strategies, and resource allocation to prevent conflicts and ensure data integrity. By simulating concurrent access scenarios, testers can identify bottlenecks related to parallel processing and resource contention.

Scalability Testing: Scalability testing evaluates the system’s ability to handle increasing loads by adding resources or scaling horizontally. It involves analyzing how performance metrics such as response time, throughput, and resource utilization change as the system scales. Scalability testing helps organizations make informed decisions about infrastructure upgrades, resource allocation, and capacity planning to support growing user demands.

HTTP-Based Load Simulation Explained

HTTP-based load simulation, also known as protocol-level testing, involves generating HTTP requests to simulate user interactions with the system. This approach focuses on evaluating the performance of web servers, APIs, and backend infrastructure by directly emulating the communication protocols used in web transactions.

In the early days of our digital era, HTTP-based testing was widely favored. However, with the emergence of advanced web client technologies, such as those used in modern web 2.0 applications, this method has become outdated. Similarly, traditional performance testing tools like JMeter have also lost relevance. Unlike modern applications, which heavily rely on client-side scripts, HTTP-based tests overlook these scripts, rendering them ineffective for accurately measuring performance. Additionally, the lack of client-side generated session IDs restricts the simulation of complex use cases at the protocol level.

Although HTTP-based tests incur minimal overhead on load injection machines and can handle up to 800 simultaneous sessions, they struggle with complex protocol-based scenarios. Performance engineers must contend with dynamic parameters like cookies and session IDs, which can complicate test implementation. Furthermore, changes in web form names upon system updates often lead to failures in HTTP-based scripts.

Sample Script

The sample script below highlights the very technical nature of those scripts. If a technical attribute of your application changes, you must rewrite the whole script, which is easier said than done.

//sample protocol level script
transaction TMain
var
hContext: number;
begin
WebPageUrl(“https://lab3/st/”, “Greetings”);
WebPageStoreContext(hContext);
WebPageLink(“Join the experience!”, ” – New Visitor”);
WebPageSubmit(“Continue”, CONTINUE001, “Main menu”);
WebPageLink(“Products”, “ShopIt – Products”);
WebPageLink(NULL, “ShopIt – Product”, 3);
WebPageSubmit(“Search”, SEARCH001, ” – Search”, 0, NULL, hContext);
end TMain;

dclform
CONTINUE001:
“name” := “jack”,
“New-Name-Button” := “Continue”;

SEARCH001:
“search” := “boot”;

Protocol-level level scripts are good for component level tests in continuous integration environments, and due to their low footprint on load injection machines, are the perfect setting for stress tests.

Advantages

Lightweight and efficient: HTTP-based load tests focus solely on network communication, making them less resource-intensive compared to browser-based approaches.

Scalability testing: These tests can evaluate the server’s capacity to handle a high volume of HTTP requests without the overhead of rendering web pages.

Headless Browser-Based Load Simulation

Headless browser-based load simulation takes a more comprehensive approach by emulating user interactions at the front-end level. Unlike HTTP-based tests, which focus on backend infrastructure, this methodology replicates how real users interact with web applications by rendering and executing JavaScript code.

As web technologies evolved with web 2.0, testing faced big challenges. Traditional testing struggled to handle rich browser applications because it couldn’t simulate client-side logic. So, headless browsers like HtmlUnit, PhantomJS, and SlimerJS came into play, offering real-browser advantages without the heavy GUI.

These headless browsers are now widely used in test automation and performance testing. While some companies built their own, it’s easier to rely on community-supported options to keep up with browser updates. Using headless browsers comes with a cost: a typical server can handle up to eight simultaneous sessions.

Creating and customizing test scripts isn’t too tough, especially for those with basic coding skills. But not all headless browsers offer visual replay, making debugging trickier without visual feedback.

Sample Script

In the sample script below a simple post request is executed. You need Java programming skills to customize such test scripts.

//sample phantomjs script
“use strict”;
var page = require(‘webpage’).create(),
server = ‘https://posttestserver.com/post.php?dump’,
data = ‘universe=expanding&answer=42’;

page.open(server, ‘post’, data, function (status) {
if (status !== ‘success’) {
console.log(‘Unable to post!’);
} else {
console.log(page.content);
}

phantom.exit();
});

With this consideration in mind, headless browsers are the way to go if you have programming skills and you are using a solution that allows visual script replay.

Advantages

Realistic simulation: Headless browser-based tests provide a more accurate representation of user interactions, allowing organizations to identify front-end performance bottlenecks and user experience issues.

End-to-end testing: These tests encompass both front-end and back-end components, providing a holistic view of the system’s performance from the user’s perspective.

Real Browser-Based Load Simulation

Real-browser-based load simulation represents the pinnacle of realism in performance testing, as it employs actual web browsers to simulate user interactions. This approach offers unparalleled accuracy in replicating user behaviors and frontend performance.

Web 2.0 applications utilize various technologies like JavaScript, Flash, AJAX, and CSS. To accurately measure end-to-end response times, a full browser is necessary. Real browser-based performance testing ensures the site’s functionality and speed align with user expectations.

This testing solution captures loading times for images, JavaScript, CSS, and more, often presenting data through waterfall charts to visualize component load times. While real browser-based testing requires slightly more resources, it provides a more realistic simulation compared to headless browsers. Therefore, it’s the preferred method for testing. Implementing and maintaining test scripts is straightforward since user actions are accurately reflected, and visual replay aids debugging.

Sample Script

In the sample script below, the browser opens a URL, inserts the user’s password, and clicks the login button.

//sample real browser-based script
transaction TMain
begin
BrowserStart(BROWSER_MODE_DEFAULT, 800, 600);

//navigate to the login site
BrowserNavigate(“https://demo.com/TestSite/LoginForm.html”);
//set the authentication for the secure site
BrowserSetText(“//INPUT[@name=’user’]”, “User1”);
BrowserSetPassword(“//INPUT[@name=’pwd’]”, “Password1”);
//Login
BrowserClick(“//INPUT[@value=’Login’]”, BUTTON_Left);
end TMain;

After all, real browser simulation is useful for realistic end-to-end load tests. However, don’t use it for stress testing because the footprint on the load injection server is too high.

Advantages

Authentic user simulation: Real-browser-based tests closely mimic genuine user behaviors, offering insights into frontend performance and user experience across different browsers and devices.

Comprehensive testing: By leveraging actual browsers, organizations can uncover issues related to browser compatibility, rendering inconsistencies, and client-side script execution.

Comparison of Load Testing Types

Obviously, there are good reasons and situations for protocol, headless, and real browser-based user simulations. The matrix below provides some guidance on when to choose the appropriate testing approach.

We hope you found this article helpful in understanding load simulation and performance testing types better! If you have any questions about running load and stress tests, or if you’re curious about the LoadView solution, feel free to reach out to our team or sign up for our free trial. When you sign up for a free trial with LoadView, we’ll give you some complementary load tests so that you can get started right away.