Load testing tools is critical in an era where the latest software is being developed every day. No matter how well you code or how thorough your initial testing process is, something will always slip through the cracks.
That is why load testing is so critical. While there are numerous commercial tools available to assist you with this process, open-source alternatives are also available.
What is Load Testing, Before knowing about the Load Testing Tools
Load testing is a subset of performance testing that involves multiple concurrent users running the same program at the same time. This is done to determine whether a system’s infrastructure can handle the load without sacrificing functionality or with acceptable performance degradation.
Load testing is used to determine whether:
- When compared to specification, user requirements, or KPI, the response time returned from critical actions in your application is accepted.
- Are your key business functions functioning properly under high load?
- Is your infrastructure built to scale under stress?
- In general, performance testing tools are critical to customer satisfaction. If your application fails to meet your customer’s expectations or all service level agreements, they will go to your competitor.
One of the most misunderstood aspects of performance testing is load testing versus other tests. There are numerous load testing best practices to be aware of before using any of the tools listed below.
Here is our comprehensive list of the top open-source and free load-testing tools for your load and stress-testing performance engineering efforts in 2022.
Here are some options, along with a tool comparison, to help you decide which tool to use for your application performance efforts in 2022.
The List of Load Testing Tools
This list only includes open-source and free options for the best load testing tools for automated performance testing and API load tests, so you can download them and get started right away.
JMeter is the most widely used open-source performance tool for measuring load time. Apache JMeter describes itself as a Java application designed specifically for load testing tools and capable of measuring application performance and response times.
JMeter was designed to be an open-source alternative to LoadRunner, so it has a plethora of sophisticated features. It’s a thick Java client app that relies heavily on right clicks. It’s a little strange, but it has a lot of power. JMeter also has all of the features that a professional load tester requires.
- The ability to perform performance testing on a variety of technologies using protocols such as Java Objects, Web HTTP/HTTPS, SOAP and Rest Services, FTP, and Databases with JDBC.
- An excellent IDE for recording, building, and debugging performance tests.
- Groovy is the default programming language in JMeter since version 3.1.
- One of the more widely used load-testing tools
- It can be set up to help with mobile app performance testing.
- You can write your performance tests in Java and use the IDE’s autocompletion and inline documentation with jmeter-java-dsl.
- On GitHub, it currently has over 6k stars.
Taurus (the Bull)
Taurus, while not technically a load-testing tool, functions more as a wrapper on top of other solutions, hiding the complexities of running performance tests.
Taurus’s strength is that it allows you to write your tests in YAML. A full-fledged script can be described in about ten lines of text, allowing teams to describe their tests in a YAML or JSON file. YAML is a human-readable, edible approach for describing a test in a simple text file.
This is a significant improvement over the previous requirement of bringing up a significant, heavy vendor-specific record and scripting tool for load time measurement.
- More team members should be able to contribute to performance tests as a result of this. Furthermore, because your test cases are written in YAML, the tests are much more readable, making code reviews easier.
- Taurus effectively integrates performance testing into your CI/CD pipeline.
- Taurus adds an abstraction layer to JMeter and other tools such as Locust, Gatling, the Grinder, and Selenium.
- On GitHub, it currently has 1.7k stars.
Locust is a user-friendly, distributed user load testing tool that can assist you in capturing response times. So, what programming languages does it employ?
Python is the best one. It is used to aid in the performance testing of websites or other applications.
JMeter vs. Locust
- JMeter, for example, is based on a thread-based architecture that consumes a lot of resources. Locust, on the other hand, employs an event-based approach that consumes fewer resources.
- Rahul Solanki, a technical leader at BlueConch Technologies, told me that when he compared Locust to JMeter, the number of resources that Locust consumes was roughly 70% less.
- Locust uses the term “swarm” instead of “load generators,” as in you can direct a swarm of locusts to put a load on your website.
- You can specify the desired behaviour for each Locust instance. It also allows you to monitor the swarming process in real-time via a web UI.
- You can easily scale the number of users you need to emulate by using straight Python to create your test scenarios.
- It has an amazing web-based user interface that is extensible.
- Excellent for API testing.
Fiddler with BlackWidow and Watcher
This may appear to be an unusual combination on a list of website performance tools.
However, in a previous PerfGuild conference session, performance engineering expert Todd DeCapua recommended using Fiddler with Watcher and BlackWidow to create a quick-start automation testing solution. Fiddler can do a lot of things, but it’s best described as a packet capture tool.
While Fiddler is not a load-testing tool and solution, it does a lot of things that help you debug website issues, and with one of its many extensions, you can do even more.
- Troubleshooting problems with your web application Security testing
- Performance appraisals
- Most computers and devices can be used to debug web traffic.
- There are numerous integration features.
- This is useful for locating performance bottlenecks.
- Fiddler is already a well-known tool among developers. Many people use it for debugging, and viewing the HTTP requests that their computer sends to a service or website.
Watcher is a security add-on for Fiddler that allows you to quickly obtain security results. BlackWidow is a web crawler that allows you to point it at a web address and then drill down into the results.
For someone who is just getting started in performance engineering, these three tools combined can provide a great way to get that free look and feel as well as results that would otherwise be difficult to obtain quickly. Todd had a session at a previous PerfGuild online conference where he demonstrated this approach.
According to its GitHub page, nGrinder was created to be an enterprise-level performance engineering solution. It was designed to simplify stress testing and to serve as a platform for creating, executing, and monitoring tests.
- To create test scenarios and stress the JVM using multiple agents, you can use Jython or Groovy.
- It can extend tests with third-party libraries such as jar and py.
- Allows you to keep track of your performance agents’ load generation status.
- After tests, take care of automatically collecting test results from distributed agents.
- On GitHub, it currently has 1.3k stars.
The Grinder is a framework written in Java. It offers simple-to-run and -create distributed testing solutions that use multiple load generator machines to capture end-user response times. As a result, there are no virtual user restrictions to worry about.
- This Load testing tool can be performed on any system that has a Java API.
- A nice graphical user interface console
- It handles client connection and cookie management automatically.
Gatling is a Scala, Akka, and Netty-based stress test tool. This modern architecture approach enables you to test and measure your application’s end-to-end performance and easily scale up your virtual users.
- It has a simple but effective DSL.
- Simple to expand
- If you’re interested in Scala and its advantages, this is the load-testing tool for you.
- It includes a scenario recorder.
- Allows you to perform performance testing using a shift-left code approach.
- On GitHub, it currently has 5.1k stars.
- API for clean scripting
- Offers distributed and cloud execution
- REST API orchestration is a cool feature.
- On GitHub, it currently has 11.7k stars.
Tsung is a multi-protocol distributed load testing tool that is open source.
- It has an HTTP recorder and can monitor a client’s CPU, memory, and network traffic.
- HTML reports and graphs are included.
- HTTP, XMPP, LDAP, and other protocols are supported.
- On GitHub, it currently has 2.1k stars.
Siege is a command-line tool for HTTP load testing tool and benchmarking. It was created to assist developers in stress-testing their code.
- Basic authentication, cookies, HTTP, HTTPS, and FTP protocols are all supported.
- allows its users to attack a server with a set number of simulated clients. These clients declare the server to be “under siege.”
- Excellent for a simple, brute-force performance testing tool.
- On GitHub, it currently has 4k stars.
Bees Armed with Machine Guns bees armed with machine guns
This is probably one of the coolest-sounding performance testing tools on this list, created by the Chicago Tribune. Bees with Machine Guns bills itself as a utility for arming (creating) a large number of bees (micro Amazon EC2 instances) to attack (load test) targets (web applications).
This load or volume testing tool can quickly assist you in load testing tool a site for high traffic. Make use of Amazon EC2. On GitHub, it currently has 6K stars.
LoadRunner is one of the most commonly used enterprise-wide load testing tools, but many of these open-source tools can provide you with the majority of the functionality you require. Furthermore, the majority of these tool protocols can be used for both performance testing and performance monitoring.
Fortio is a fantastic load-testing tool library, command-line tool, advanced echo server, and web UI written in Go (Golang). This tool allows you to set a query-per-second load and record latency histograms and other useful statistics.
- It is quick.
- Minimalist footprint (3Mb docker image, minimal dependencies)
- Go library that can be embedded
- Can record latency histograms and other useful statistics.
- On GitHub, it currently has 1.8k stars.
Front-end performance should not be overlooked.
Puppeteer WebPerf can be used to collect web performance stats such as a page load trace, a dev tools trace with screenshots, runtime performance metrics, and much more.
For more information, see my complete front-end performance testing guide. On GitHub, it currently has 1.4K stars.
The Flood developed this open-source solution to aid in the simulation of user behaviours through a real-time browser load-testing tool. Element is an open-source playwright that makes use of a load-testing tool that runs in the browser. Typescript is used to write test scripts.
- You can use it against your Web app by opening a browser and interacting with page elements in the same way that your customers do.
- This method can assist in identifying user-facing performance issues.
- It’s written like a functional test script, but with Flood, you can quickly run load-testing tool scripts on as many nodes in the Cloud as you want.
- It is one of the few open-source tools that allows you to create performance testing using real browsers in order to simulate how real users interact with your application.
Artillery.io is an open-source application with a premium service opt-in to create load tests that simulate thousands of users.
- per second requests
- record the average response time
- as well as throughput.
- Peak performance testing for your back-end application to ensure stability and reliability.
- HTTP, Web Socket, Socket.IO, Kinesis, and HLS are among the protocols it supports.
I hope this comprehensive post with a list of the best Performance and Load testing tools helps you choose the right tool for your project.
The smartest approach is to use trial versions of the relevant tools to determine how well they fit your needs.