The Ultimate Open-source Load Testing Tools for Developers

The Ultimate Open-source Load Testing Tools for Developers

As websites and web applications grow more complex and feature-rich performance is an important issue for both developers and users alike. There are studies that show that faster websites lead to increased engagement of users, higher sales, and more visitors, it's crucial to take note of how quickly you can get your site to your visitors and have it in their browser.

The most common term used to describe this field of study is web performance optimization and over the last couple of years, a variety of best practices, methods, and techniques have been created to enhance the experience of browsing. A lot of these strategies focus on reducing the download size of websites by optimizing JavaScript and restricting the number of HTTP requests that a webpage requires.

We'll discuss the other aspect of web performance: how quickly will your server be able to respond to user requests? We'll go over the general landscape of load tests, go through a strategy to determine the server's highest response time, and then examine some open-source load-testing software.

Sun Technologies is a world-class load testing service provider for many organizations across the globe. Our team of experts analyses the overall behavior of web-based, client-server applications thoroughly to identify the real-world capacity of the applications under varying loads as well as measuring and validate the apps for a better user experience by fixing errors in the early stages.

Read our case study to know how we performed load testing for a leading financial enterprise in the US.

What is Load Testing in Software Testing?

Load Testing is a kind of Performance Testing that determines the performance of a software application or product under real-world load conditions. The purpose of load testing is to determine the behavior of the software when multiple users are using it simultaneously. It's the reaction to the system as measured under different conditions of load. The load test is performed for extreme and normal load conditions.

Types of Load Testing Before you put any algorithm or software into the decision-making process it is important to make certain that it's working. To ensure that your tools work, they should require a variety of tests and measurements, with one of the most important is load tests. There are many kinds of load testing and each has specific purposes.

The general rule is that load testing is a way of measuring the performance of your system in various situations. Since data science is an expansive, ever-changing field, knowing these parameters is crucial.

To help you understand there are five different types of load testing and the times you should be using these types of tests and when you should apply them.

Stress Testing Stress tests are probably the most well-known type that load tests. They are the process of pushing your system to its limits to find out if they fail, whether the failure is due to data corruption, leaks in memory, or another issue. It is possible to do this by increasing any factor from concurrent users and data throughput, up to the highest levels. Stress testing will reveal the upper limits of your system are, and also what causes the first break.

Spike Testing Spike testing is similar to stress testing however, it is focused on short periods in volume. This is why it has the term. In these tests, you increase the throughput to determine the response of your system.

It's not necessary to find the breaking point, however, you're evaluating whether your system is able to withstand the sudden increase in the number of measurements.

There are many algorithms that do not need the test of spikes, however, yours could be based on the intended purpose. Systems that might encounter spikes in real-life situations such as Black Friday for an e-commerce site, absolutely require these tests. If you don't have them, they may create a flawed system and not even realize it.

Volume Testing Volume testing is also known as flood testing, it involves feeding large amounts of data to your system and seeing what it does. If you're developing the solution to any large data application, testing in volume is essential.

Testing in volume is a great way of uncovering bottlenecks within your system. It also reveals its capabilities, such as stress testing. These findings can aid any algorithm working with a lot of data but is vital in the case of big data. If you do not test it in the volume of an application that uses big data then it might not stand against real-world usage.

Load Banking Testing The data centers hosting your apps may benefit from load tests too. Tests on load banks for generators use the device known as load bank that draws different levels of power from it. It will be able to determine the way it performs in different levels of energy consumption which your center may test it under.

The regular testing of your load banks can take just 30 minutes. It is vital for the security of the continued operation of your data center. These tests will reveal whether your generator is prone to failure under certain conditions so that it can be repaired or replaced prior to compromising your data.

It's easy for people to ignore load bank tests because it's not directly applicable to your application, however it could be an important tool.

Soak Testing The majority of load tests uncover issues that can be discovered within the first few hours after the test. The system might have to run longer than that, and certain issues will only manifest over time.

This is the point where soak testing comes into play.

The process of testing for soak often referred to as endurance testing, assesses the system's performance over a long time. It can reveal whether performance decreases with time, in the event of bottlenecks occurring after a few days of usage, and even more. If you are planning to operate your system for months, weeks, or even all day long it is recommended to test it in a soak.

Soak testing generally involves using testing software to simulate these lengthy durations in a shorter time. For instance, you can do 30 days of testing in just two days which will save you time.

Load Testing Methodology • • • •

Initiate with a solid strategy Increase the size of your load testing Adopt complete automation Make your procedure simpler

Benefits of Load Testing • • • • •

Reduces the risk of failure Improves scalability Customer satisfaction is higher Reduces the chance of a system outage Recognize inefficient code

10 Best Load Testing Tools 1. LoadUI Pro 2. WebLOAD 3. Neoload 4. HP Loadrunner 5. LoadNinja 6. StresStimulus 7. LoadView 8. Apache JMeter 9. ReadyAPI Performance 10. K6

Best Practices for Performing Load Testing •

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Always test the stability of your application prior to starting a load test. The application should be declared to be functionally stable with the help of the functional testing team. All major flaws must be addressed and verified before the build is copied into Load Test environment.

Check you are in a Load Test environment replicable or is similar to the actual environment, such as the amount of servers used, Load balancers, server configurations, and firewalls.

Make sure that your test results are unique, and you have all test data copied into the load environment prior to running the load test.

Create the test scenarios so to replicate the real-time user's actions in production.

Create the workload based on the user load as well as business flows. In case of an older application check if there is an opportunity to talk to the management team about the business flow and user load.

Gather all important metrics such as Response Time, Hits per second, throughput CPU, Memory, Running Vusers and Network.

Conclusion Before you begin a load test, it is important to choose the correct workload. Find the footprint of the virtual user so that you can prepare the proper amount of load generators, and the distribution of virtual users between them. You must create the data that virtual users will utilize, and you'll need to set up the hardware, environment servers, or whatever that you are testing regardless of the test tool itself.

This is the case for any test of performance that is conducted with the help of tools such as JMeter K6, loadNinja, and others. Keep in mind that large-scale load testing isn't an easy task. It is essential to be able to have all participants available to assist and review the results as the test runs and to identify optimization steps.

Contact us today for the best Load Testing Services.