When it comes to load testing tools, there is a recent tool called PFLB which I received a comparison with the most popular one: JMeter. Each has its own strengths and weaknesses, making them suitable for different scenarios. Let’s delve into a comparison between the two.
| PFLB | JMeter | |
Support | – HTPS(S) – SOAP – REST – FTP – LDAP – WebSockets – SMTP/POP3/IMAP – Citrix ICA | – HTTP – FTP – JDBC – SOAP – LDAP – TCP – JMS – SMTP – POP3 – IMAP |
Speed to Write Test | Fast | Slow |
Support of “Test as Code” | – Limited Support – Scripting – Control Version – CI/CD Integration – Reusability | – GUI oriented – Possibility to create scripts, but too complex and lack of documentation – Weak (Java) – Hard to maintain |
Ramp-up Flexibility | User-Friendly through GUI | Plugins available to be able to configure flexible load |
Test Result Analyzing | Yes | Yes |
Resource Consumption | Optimizing resource usage involves properly configuring test scenarios and monitoring performance to adjust as needed. | Heavy to run tests with multiple users on a single machine, more memory consumption |
Easy to use with Version Control Systems | Yes | No |
Recording Functionality | Yes | Yes |
Distributed Execution | Yes | Yes |
Load Test Monitoring | It reduces memory consumption through asynchronous logging, cloud-based infrastructure, and integration with specialized monitoring tools. | Ability to monitor a basic load |
PFLB is most used when you need:
- Scalability: PFLB tool offers cloud-based load testing, allowing users to scale tests to simulate millions of users without worrying about local resource limitations.
- Integration: It integrates seamlessly with other monitoring and APM tools (e.g., New Relic, Dynatrace, Datadog), providing comprehensive performance insights and real-time analytics.
- Ease of Use: PFLB tools are easy to use, with intuitive interfaces and detailed reports, making it easy for teams to set up, run, and analyze load tests.
- Enterprise-Level Support: PFLB provides robust support and customization options for enterprise clients, ensuring that specific performance testing needs and requirements are met effectively.
JMeter solves some specific problems:
- Identifying Performance Bottlenecks: JMeter helps detect slow or underperforming parts of an application by simulating various load conditions and monitoring response times.
- Scalability Testing: It evaluates how an application scales with increased load, ensuring that the system can handle expected traffic and identifying any points of failure.
- Concurrent User Simulation: JMeter can simulate multiple users accessing the application simultaneously, allowing testers to observe how the application behaves under concurrent usage.
- Regression Testing: It can automate performance tests as part of a continuous integration process, ensuring that new code changes do not degrade application performance.
Thanks to Victoria from pflb for sending me this comparison !
Rafaela Azevedo 