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  • Writer's pictureCraig Risi

The Pros and Cons of Different Test Tools – JMeter




When it comes to testing and automation, we may focus on tools from a UI, API, or performance perspective – but in essence, there are a lot of tools that can do well in all of these areas. Some of the biggest tools we focus on in my UI testing analysis like UFT and Tosca are particularly good at handling both UI and API automation. However, when it comes to true versatility, perhaps no testing tool is as versatile as JMeter.


Initially developed as an open-source tool aimed at performance testing, JMeter has evolved to be used as a tool that can handle all forms of test automation too. And because it is powered by a JVM, it is not just limited to desktop or web automation as some other open-source tools but can automate across all application types.




And one of the biggest benefits this bring is for complex end-to-end testing scripts. By using JMeter, teams can interact with APIs, DBs, and applications all within one script. And while this type of automation is not recommended for most testing needs, for those few complex testing solutions where this sort of application switching might be required, JMeter can allow teams to automate their full workflow. And with a bonus, provide a level of performance testing throughout the process too.


It has perhaps not gained as much recognition in the development community for its test automation skillsets and might be seen as a jack-of-all-trades and master of none, but it’s still incredibly effective at what it does and for companies looking to embrace opensource tooling but wanting to just stick with one tool, JMeter is certainly one of the best tools to consider. It might not have the complete set of tools available in each of the respective testing departments, but it provides all the critical ones you will likely need.


The tool is comprehensive in what it tries to achieve, but because it perhaps doesn’t specialize in any specific skill sets, you may need additional tooling to find the full value out of it. For instance, while JMeter can be used to create test plans that can be executed and automated, it's not nearly as effective as many other tools and you will likely want to make use of a separate test management tool to properly manage its scripts. Additionally, while it might have been developed as a performance testing tool, it is very light on actual real-time monitoring and so you will still need to collect data on the underlying system performance from other sources to get the full picture of your application performance. Though to be fair, many performance tools struggle to do this effectively.


Example of how JMeter would work with containerization through an Azure Pipeline.


The other drawback to the tool is that its reliance on a JVM makes it more ineffective than many other similar tools for running in containers. While it can be easily containerized, it requires a large container footprint, and because it’s resource intensive, it's often best left operating outside your CI/CD pipelines and executing through a purpose-built VM. Given that JMeter is already an excellent player at operating across different application layers, it is often best utilized post-deployment phase anyway.


Below is a list of all that the tool offers to understand exactly what the tool is capable of:


Test Plans: JMeter uses a hierarchical structure called "Test Plan" to organize and manage your performance tests. A test plan can include multiple elements like thread groups, controllers, samplers, and listeners.


Thread Groups: Thread groups represent virtual users or threads that simulate real user behavior on your application. Each thread group can have a specified number of users, ramp-up time (time taken to start all users), and loop count (how many times to repeat the test).


Controllers: Controllers define the logic for how requests are sent to the server. There are various types of controllers like Simple Controllers, Loop Controllers, and more, each serving a specific purpose in controlling the flow of requests.


Samplers: Samplers are responsible for sending requests to the target server. JMeter supports various types of samplers, such as HTTP Request, JDBC Request, FTP Request, and more, which allow you to simulate different types of interactions with your application.


Listeners: Listeners collect and display the results of your performance tests. They provide various types of output formats like tables, graphs, and charts to help you analyze the test results visually. Some popular listeners are Summary Report, Aggregate Report, and Graph Results.


Assertions: Assertions are used to validate the responses received from the server. They help you ensure that the responses meet the expected criteria, such as specific text in the response or response time within a certain range.


Timers: Timers are used to simulate user think time between requests. They add delays to your test to simulate real-world scenarios where users don't interact with the application immediately.


Ramp-Up: The ramp-up time specifies how long it takes to start all the users defined in a thread group. This helps simulate a gradual increase in load, which is more realistic compared to an instant influx of users.


Throughput: Throughput is the number of requests processed by the server per unit of time. JMeter provides various features to measure and analyze throughput during performance tests.


Scenarios: JMeter allows you to create complex test scenarios by combining different elements like thread groups, controllers, and samplers. This enables you to simulate real-world usage patterns and evaluate how your application performs under different conditions.


JMeter can be run in both GUI mode and non-GUI (command-line) mode. While the GUI mode provides an interactive environment for creating and editing test plans, the non-GUI mode is typically used for running tests in a more resource-efficient manner, such as on remote servers.


Overall, Apache JMeter is a powerful tool for assessing the performance and scalability of your applications, helping you identify bottlenecks, optimize resources, and ensure that your systems can handle the expected load effectively.


History of JMeter

  • 2001: The JMeter project was initially created by Stefano Mazzocchi and Peter Lin as part of the Jakarta Project, which was an effort by the Apache Software Foundation to develop and maintain open-source Java-based tools.

  • 2002: JMeter 1.0 was released as an open-source project under the Apache License. It was designed primarily for load testing and performance measurement of web applications and services.

  • 2003: JMeter 1.8 was released, introducing various enhancements and improvements, including support for additional protocols and more advanced features.

  • 2004: JMeter 2.0 was a significant release that introduced a complete rewrite of the codebase, aimed at improving performance, scalability, and extensibility. This version also brought about the concept of a "Test Plan" hierarchy.

  • 2007: JMeter 2.3 was released, further refining and expanding the tool's capabilities. This version included various bug fixes, improvements, and new features.

  • 2011: JMeter 2.5 was a notable release that introduced several enhancements, including improved scripting support and better integration with other testing tools. This version continued to solidify JMeter's reputation as a versatile performance testing tool.

  • 2013: JMeter 2.10 was released, featuring better support for mobile application testing, improved handling of CSV files, and numerous bug fixes.

  • 2014: JMeter 2.11 brought several new features and improvements, such as enhanced HTML reporting and better support for WebSocket testing.

  • 2015: JMeter 3.0 marked a significant milestone with improved UI design, more efficient handling of test plans, and better reporting capabilities. It also introduced support for the new Java 8 features.

  • 2016-2020: Subsequent releases continued to refine and expand JMeter's capabilities, introducing features like support for the HTTP/2 protocol, enhanced distributed testing, and improved scripting options.

  • 2021: Apache JMeter 5.4, continued the trend of enhancements and bug fixes. It introduced support for Java 11 and included various improvements to the user interface and reporting capabilities.

Pros of Using JMeter

  • Open-Source: JMeter is open-source software, which means it's freely available and can be customized to fit your specific testing needs.

  • Versatility: JMeter supports a wide range of protocols and technologies, including HTTP, HTTPS, FTP, JDBC, SOAP, REST, WebSocket, and more. This versatility makes it suitable for testing various types of applications and services.

  • User-Friendly Interface: JMeter provides a graphical user interface (GUI) that makes it relatively easy to create and manage test plans, set up test scenarios, and visualize test results.

  • Scalability Testing: JMeter supports distributed testing, allowing you to simulate a large number of users by distributing the load across multiple machines. This makes it suitable for testing applications under high loads.

  • Plugins and Extensibility: JMeter has a vibrant community that has developed a wide range of plugins to extend its functionality. These plugins can add features and protocols that might not be available out of the box.

  • Scripting Support: While the GUI is user-friendly, JMeter also supports scripting in languages like Groovy, JavaScript, and Beanshell. This can help create custom logic and advanced test scenarios.

  • Detailed Reporting: JMeter provides various built-in listeners and reporting tools that help you analyze test results and identify performance bottlenecks.

  • Integration with CI/CD: JMeter can be easily integrated into Continuous Integration and Continuous Deployment (CI/CD) pipelines, allowing you to automate performance testing as part of your development process.

Cons of Using JMeter:

  • Steep Learning Curve: While the GUI is user-friendly, JMeter's advanced features and concepts can have a steep learning curve, especially for those new to performance testing.

  • Resource Intensive: Running large-scale tests or complex scenarios in GUI mode can be resource-intensive, potentially affecting your system's performance. Running tests in non-GUI mode is recommended for better resource management.

  • Limited Realism: JMeter simulates user behavior, but it might not capture every nuance of real-world user interactions, leading to limitations in realism.

  • Complex Scenarios: While JMeter can handle complex test scenarios, setting them up correctly might require a good understanding of the tool's architecture and features.

  • Limited Browser Interaction: Unlike some other performance testing tools, JMeter doesn't provide native browser interaction, which might be required for certain types of performance testing.

  • Dynamic Load Modeling: Modeling dynamic user behavior, where the number of users increases or decreases based on specific conditions, can be challenging in JMeter.

  • Lack of Real-Time Monitoring: JMeter lacks real-time monitoring and analytics capabilities during test execution, which can make it difficult to identify issues as they occur.

When to use JMeter

  • When performance testing is critical to you and you want to streamline both your functional and performance testing through one tool.

  • You have a strong, technically-minded testing team that is comfortable in working with Java and testing frameworks

  • You don't mind your tests taking up big container space and running a little slower.

In summary, JMeter is a powerful and versatile tool for performance testing, but it's important to consider its learning curve, resource usage, and potential limitations when deciding whether to use it for your testing needs. It's also a good idea to explore other performance testing tools to see if they might better suit your specific requirements.

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