Apache JMeter has its own pros and cons when compared to other tools. It is easy to use the tool and it has open-source capability so we can build our custom scripts and execute them. It provides other capabilities, such as integrating a database and connecting to other application servers for monitoring and related functions. We use dynamic HTML reporting, which helps us in testing analysis by pinpointing the bottlenecks based on the reports. We can identify the specific areas that need attention, troubleshoot them, and report to the development team. The user-friendly GUI for creating and managing tests makes it very easy to drag and drop samplers. For example, if you want the HTTP sampler, you can drag and drop it and use it. For configurations, we have other samplers. For results, we have the view results samplers that we can also drag and drop. The UI is good in comparison with other tools. Regarding integration with CI/CD pipelines, we can create Apache JMeter scripts and use the Docker image. From the image, whatever scripting we have done can be connected. We can use the CI/CD pipelines and connect them with Jenkins tools and GitHub. Then we can create the pipelines and automate the end-to-end flow. For connecting Jenkins to Apache JMeter, JMeter plugins are available, and we have used them. Apache JMeter also has some third-party plugins, which are not native samplers. If we want to use custom test executions, we definitely use all the different plugins available in Apache JMeter. The capability to simulate users has impacted testing resources and outcomes as Apache JMeter is based on Java, which has a limit to the users in a particular load generator. Apache JMeter provides distributed load testing where you can connect multiple PCs in a master and slave concept, allowing you to pump the load with any number of users. In the past, I have done load testing with 10,000 users by connecting the Apache JMeter distributed network in BlazeMeter. There is a cloud version available, the updated BlazeMeter, and I used that. It is very easy to launch load generators in BlazeMeter, and then we can run the test, scaling up beyond 10,000 users.
