Let’s keep going where we stayed about Jmeter and Locust . If you didn’t read Part1 you can reach here.

6. Script Recording

Script recording is a quick and easy method to construct a simple test template, which you can then tidy up and modify to make it easier to maintain. If you need a quick solution and need to execute a specific load depending on repeated actions, script recording comes in handy. You don’t want to waste time writing a script in such a circumstance, especially if you won’t need it again. If you’re planning to conduct reliable performance tests again and over, script recording isn’t advised because they’re not very stable.

JMeter has a significant edge in this area since it includes built-in script recording capabilities, whereas Locust does not. Furthermore, there are several third-party plugins that can record scripts for JMeter.

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7. Load Tests Monitoring

JMeter and Locust both have excellent built-in features for monitoring performance scripts and analyzing test results. Listeners are a collection of JMeter components. Each listener is responsible for a certain sort of monitoring:

JMeter-Locust-comparison-4
JMeter-Locust-comparison-5

JMeter comes with a wide number of built-in listeners, and you can also add new listeners to the default library. JMeter Listeners are the subject of this blog series, which begins here. On the other hand, consume a significant amount of the system’s resources. As a result, JMeter is frequently used in a non-GUI mode with no listeners, and the monitoring is done via third-party tools like Loadium.

Locust, on the other hand, has a limited set of monitoring tools. Locust, on the other hand, offers virtually all of the information needed to monitor a basic load. During the execution of a script, Locust sets up a basic HTTP server where you may see all of the monitoring results:

JMeter-Locust-comparison-6

In compared to JMeter, Locust monitoring consumes fewer resources on your computers. That’s why Locust outperforms JMeter since you can utilize built-in monitoring even if you’re simulating a large number of people. On the other side, default monitoring does not give the level of detail that third-party solutions can. As a result, you should probably look at other script monitoring solutions.

Using the Loadium reporting, which provides great real-time reports with the opportunity to store them for later comparison, is one of the easiest methods to monitor and evaluate your test results. You may get a general understanding on this article.

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Head to Head Comparisons Between JMeter vs LoadRunner

Take a look at the following table to see how JMeter and Locust compare in terms of features and capabilities:

LOAD TESTING REQUIREMENTJMETERLOCUST
Operating SystemAny

Any

Open SourceYes Yes
GUIYes, with non-GUI mode available

No

Execution MonitoringConsole , File, Graphs, Desktop client, Custom plugins

Console, Web

Support of “Test as Code”Weak (Java)Strong (Python)
In-built Protocols SupportHTTP, FTP, JDBC, SOAP, LDAP, TCP, JMS, SMTP, POP3, IMAPHTTP
Recording FunctionalityYesNo
Distributed ExecutionYesYes
Number of Concurrent UsersMillions

Thousands

Ramp-up FlexibilityYesNo
Test Results AnalyzingYesYes
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CONCLUSION

We are not going to claim which tool is superior since there is no better tool, as we stated at the outset. You should use Locust if you are proficient in Python, or if you simply prefer coding over creating UI tests. JMeter, on the other hand, could be a better option.

If you’re new to performance testing, it’s also a good idea to start with JMeter, because the JMeter UI immediately tells you the alternatives you have for achieving your testing objectives. Simply navigating the menu will show you which samplers you can use to generate a load, which timeouts you can use to make script pauses, and which settings you can add using the in-built configuration components. Locust, on the other hand, provides just documentation and a few code samples, allowing you to determine whether you are capable of implementing the needed load script based on your Python knowledge.

And…

Locust test coding has its own set of advantages. A version control system like Git, for example, makes it considerably easier to manage and configure performance testing for various settings. Dealing with code is preferred in these situations. Knowing Python is certainly beneficial in the case of Locust. Simultaneously, if you prefer coding over creating UI tests but aren’t familiar with the Python programming language.

However, if you need to perform a complex load involving multiple protocols, if you don’t have time to write your own samplers in Python, if you need script recording functionality, if you need to simulate a specific load with some custom ramp-up patterns, or if you simply prefer a UI desktop app for script creation, or if you don’t know Python well enough, you should use Python. However, as previously said, if you are unfamiliar with Python, JMeter appears to be the superior alternative.

We chose Loadium over Blazemeter because of its strong support with better report screens. Taking support in emergency is great value. Thank you.

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The high price of Blazemeter and the high price of its support fees caused my organization to look for another open source alternative for performance testing and continuous testing.

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We have been using the Loadium product actively for 3 years and on a daily basis with my whole team. We can easily track our performance reports. In terms of support, we can get a very fast response, most of the time, our problem is solved by the Loadium team within a maximum of 1 hour.

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