Software Load Testing Tools

[Jon Levatte]

Loadtesting is a specific sub-family of a performance test that includes many concurrent users running the same program at the same time. This is done to see whether a system infrastructure can handle the load without compromising functionality or just with acceptable performance degradation.

Front-end performance testing measures how fast your website loads and displays content for users. In contrast, back-end performance testing involves sending multiple requests to your servers to see if they can handle simultaneous requests. Most performance testing tools only test API endpoints, but tools like xk6-browser go beyond that by testing browser performance as well.

Performance testing tools, in general, are critical to customer satisfaction. They will move on to your competitor if your application performance doesn't meet your customer's expectations or all service level agreements.

Additionally, even smaller applications can benefit from load testing as it provides valuable insights into their performance capabilities and limitations under stressful situations. Regular load testing helps in maintaining and improving the performance of the software, ensuring it can handle real-world usage scenarios effectively.

Load testing vs. other tests is one of the most misunderstood parts of performance testing. And there are many load testing best practices you should be aware of before even using one of the tools listed below.

This list only includes open source and free options for the top load test software for automated performance testing and API load tests, so you can just download and get started right away without spending a dime.

WebLOAD is a comprehensive load testing tool designed to handle complex testing environments and optimize load times effectively. Developed by RadView, it is tailored for performance engineers seeking in-depth analysis and reliable results.

WebLOAD excels in performance analysis by providing detailed reports and analytics. It monitors both client-side and server-side metrics to identify bottlenecks and ensure optimal application performance under various load conditions

WebLOAD stands out as a powerful load testing solution, offering extensive features that cater to the needs of performance engineers. Its robust capabilities, combined with flexible deployment options and advanced analytics, make it an ideal choice for ensuring the reliability and efficiency of web applications under load.

For instance, JMeter can be a bit difficult to scale for a large distributed test, especially if you have to set up a bunch of machines since you have to configure them to talk to each other. There is also a host of orchestrating problems in executing large JMeter tests.

You can actually describe a full-blown script in about ten lines of text, allowing teams to describe their tests in a YAML or JSON file. The YAML is a human, readable, edible approach that enables you to describe a test in a simple text file.

But performance engineering expert Todd DeCapua, in a previous PerfGuild conference session, recommended using Fiddler with Watcher and BlackWidow to create a quick-start automation testing performance solution.

Watcher is a security add-in for Fiddler, enabling you to get some security results quickly. BlackWidow is a web crawler that gives you the functionality to point it towards a web address and then be able to drill down on results.

For someone just getting started in performance engineering, these three tools working together can provide a great way to get that free look and feel and results that one might not otherwise be able to obtain quickly.

The Grinder is a Java-based framework. It provides you with easy-to-run and -create distributed testing solutions using many load generator machines to capture your end-users response times. So you don't have to worry about any virtual user restrictions.

Load Testing ensures that your application can perform as expected in production. Just because your application will pass a functional test, this does not mean that it can perform the same under a load. Load testing identifies where and when your application breaks, so you can fix the issue before shipping to production.

Businesses and consumers rely heavily on digital applications for critical functions, so it's important to validate that it can withstand realistic load scenairos. With a higher adoption of digital applications comes higher expectations of quality, and if your application fails in production, it can become costly. According to Gartner, The average cost of network downtime is around $5,600 per minute. That is around $300,000 per hour on average. Avoiding downtime in production is essential, and load testing helps ensure that your application is ready for production.

Getting started with load testing isn't as hard as it has been historically. In the past, learning to load test - creating a realistic scenario, scripting a test, replaying a test, and analyzing test results - required an immense amount of skill and time. Plus, every load testing tool is different. So learning how to use each tool to get the test runs to function how you intend it to is always a challenge. With LoadNinja though, you can skip this whole process without sacrificing quality or test coverage.

Think like a user would. What is important to your user base? What functions of your application are critical for them? Do they use different devices? By creating realistic load tests, you're able to more closely understand how your application behaves or would behave in production with real users. Real users to a certain extent are unpredictable, so keep randomness and variablilty in mind when evaulating the steps to take in your tests. Mix up the device and browser type so you can feel confident that your application is ready for deployment.

Whether your team is adopting an agile, devops, or shift left mentality, it's essential to test early and test often. Frequently performance testing is siloed and starts when a development project is over. However, in the last few years increasing the amount of feedback throughout your software development lifecycle has proved immensely valuable in finding and fixing issues rapidly. Prioritize making performance testing, and load testing in particular, a part of your agile, continuous integration, and automation practices.

Optimizing performance requires a deep understanding your application and it's users. Identify practical & realistic tests that can reflect reality, whether that means selecting devices, browsers, number of users, etc. Plus, load tests can't start from zero. In the real world, it's unlikely that the systems you're looking to update will not be running under load already. So rather than starting from zero and incrementally adding virtual users slowly until you reach the desired load, try running tests after your systems are already under load. This way you avoid the 'false-positives' that can come from starting your load tests from zero.

To achieve realistic benchmarks and scenarios, leverage data you already have. Reusing data from your monitoring tools can help illuminate what 'realistic' means in your specific case. In most cases, monitoring tools are running from a proactive and reactive point of view - meaning you can use synthetic and real user data to map out scenarios that failed in production with a synthetic monitor and/or add interactions that your users are already taking with your application into your test scenarios. This can include user driven data, like browsers, devices, user paths, dropoff points, and system based data, like DOM load, time to first byte, and more.

After running your load tests, the first obvious step is to identify any problem areas & take the next best steps to improving performance for that component. This means correlating performance bottlenecks with code to isolate the root-cause of the problem. Oftentimes this can be difficult if you're using a traditional testing tool because it requires 'translating' the test results into metrics you can leverage to share with your development team (or to use yourself) to dig deeper into the core code instigating the issue. If you're using LoadNinja, this step is no problem, since you're load tests results are browser-based metrics, which you can inspect & debug in real time.

Finding a tool that can support your team is essential. We know that performance testing practices can take a bit of time in the release cycle, but often they are the indicators for success in production. With performance testing, you can understand how your application is going to perform in production before you deploy, so you can find and fix issues before going live. Testing reveals if your website performs differently under load, whether your code change has unexpected changes, and saves money in the long run by identifying issues before they become costly problems in production. When evaulating a load testing tool, be sure to keep the following factors in mind:

Understanding what tool will fit best into your workflows is essential. Luckily, LoadNinja helps teams load test faster without sacrificing accuracy, so teams can continuously release quality software.

Then you try to actually generate load. This is straightforward if your application is dead simple, because you can use something like Apache JMeter to generate repeated requests. If you can do this, I envy you: every system I've worked on is more complicated and requires a more intricate testing plan.

Your application gets slightly more complicated, so you then turn to tools like Gatling. These let you simulate virtual users going through scenarios, which is a lot more helpful than just besieging one or a handful of URLs. Even this isn't sufficient if you're writing an application that uses both WebSockets and HTTP calls, over a long-lived session, and requires certain actions repeated on a timer. Unless I severely missed something in the documentation, I cannot see a way to, say, setup a heartbeat that runs ever 30 seconds, do certain actions upon response to a WebSocket message, and also do some other HTTP actions, all with the same HTTP session. I haven't found a way to do that in any load testing tool (which is why I wrote my own at work, which I hope to open source if I can make the time to clean it up and separate out proprietary bits).

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