Find out what your peers are saying about Apache, Tricentis, Perforce and others in Performance Testing Tools.
With Apache JMeter, I have gained great statistics for performance and server metrics.
LoadRunner Cloud helps with risk elimination by reducing performance degradation in production, ensuring a better end-user experience.
The ROI is not necessarily cost savings. Sometimes a customer wants to use OpenText LoadRunner Cloud, or it's the only tool that will solve the problem depending on the application.
The support for Apache JMeter is excellent.
Apache JMeter has strong support through its vast Java-based community on platforms like Stack Overflow.
Apache JMeter relies more on community support.
It's important to note that OpenText has recently taken over Micro Focus.
JMeter is highly scalable, easily handling increased loads through the use of multiple servers.
This restricts the number of users and necessitates increasing load agents or distributing the script across multiple machines.
For backend automation and performance testing with web services, web APIs, and queue management systems, I would rate Apache JMeter's scalability as between eight and nine.
APICa is scalable.
It is very scalable, and on the cloud, it's even more scalable, potentially unlimited.
With load generators available, it is easily scalable to meet our needs.
The solution is highly scalable, which is its main feature.
JMeter performs exceptionally well, especially in non-GUI mode, which supports high loads efficiently.
Several necessary features still need improvements, specifically in terms of reports and additional functionalities compared to other commercial tools.
OpenText LoadRunner Cloud is extremely stable for our use case.
Currently, we need to use multiple separate JMeter instances to simulate reductions in load, which isn't ideal.
The tool needs improvements related to client-side metrics, integrating with tools like YSlow or HTTP Watch, and enhancing mobile testing capabilities.
With BlazeMeter, you can view the results in real-time.
When editing scripts, only one can be accessed at a time, risking changes affecting other folders.
In-depth analysis tools found in the standalone LoadRunner analysis, such as graph merging and setting granularity, would be beneficial.
I expect an improvement in the cloud location offering to better serve local applications, particularly to enhance testing accuracy for users in regions like Thailand.
Using JMeter helps us avoid additional costs for high-load testing since it is open-source and allows for unlimited virtual users at no extra cost.
It's a cost-effective solution.
Apache JMeter is completely free as it is open-source.
OpenText LoadRunner Cloud pricing is flexible, offering a more affordable solution compared to the more expensive on-premise LoadRunner.
It's delivering functionality, but we also use JMeter, which is free.
JMeter facilitates scripting capabilities, which include options for Groovy scripts.
It's useful for both the person conducting the test and the higher management, like project managers or senior executives, who may not know about the test.
Despite being open source, it offers features comparable to paid tools.
It is useful for both performance and automation testing, facilitating access to headers and payloads easily, enhancing scripts with dynamic values.
OpenText LoadRunner Cloud can scale in a cloud-based environment to support up to ten thousand concurrent users without capacity loss, which is not possible with on-premise solutions on personal machines.
Its LoadRunner functionality allows us to record a solution's networking protocol and replay them.
A significant difference is in its depth of analysis.
Apache JMeter is an open-source Java application that tests load and functional behavior and performance in applications. Created initially to test web applications, it has expanded its functionality to test other functions. For instance, you can test a server to see how efficiently it works and how many user requests can be handled simultaneously.
You can use JMeter to test functional performance and regression tests on different technologies. This Java desktop application has an easy-to-use graphical interface which uses the Swing graphical API. You can run JMeter on any environment that accepts a Java virtual machine, such as Windows, Linux, and Mac.
What protocols does JMeter support?
How does JMeter work?
JMeter sends requests to a target server by simulating a group of user requests. Then it collects and calculates statistics on the performance of the target. This target can be a server or an application.
You can test the performance of static resources, such as JavaScript or HTML, and dynamic resources, such as JSP, Servlets, and AJAX. It is also helpful to determine how many concurrent users your website can handle.
There are two main tests you can carry out with JMeter: load test and stress test. The load test models expected usage of a server by simulating multiple users accessing the web server simultaneously. The stress testing aims to find the maximum load capacity of the server or application.
Apache JMeter Key Features
Apache JMeter Benefits
The JMeter extensible core has numerous benefits:
Reviews from Real Users
Stephen B., I.T. Architect, Analyst, and Developer at an educational organization, says, "The scripting ability is most valuable. It is easy to use. There is a UI, and you can go in there and figure those things out. After you've got a good set of tests, you basically have a scripted document that you can grab and execute in a pipeline. It is pretty quick to set up, and you can scale it and version control it."
"I like the fact that JMeter integrates well with other tools," adds the Founder and Principal Consultant at a tech services company.
A Quality Engineering Delivery Leader at a financial services firm says, “The performance of the solution is excellent. They have designed the product so that it is very easy to configure. You can basically do anything you like with the product. It's not very restrictive. We like the fact that the technology is open-source.”
Apica offers a unified platform to remove complexity and cost associated with data management. You collect, control, store, and observe your data and can quickly identify and resolve performance issues before they impact the end-user. Apica Ascent swiftly analyzes telemetry data in real-time, enabling prompt issue resolution, while automated root cause analysis, powered by machine learning, streamlines troubleshooting in complex distributed systems. The platform simplifies data collection by automating and managing agents through the platform’s Fleet product. Its Flow product simplifies and optimizes pipeline control with AI and ML to help you easily understand complex workflows. Its Store component allows you to never run out of storage space while you index and store machine data centrally on one platform and reduce costs, and remediate faster. Observe offers modern observability data management, helping you with MELT data, effortless dashboarding, and seamless integration of synthetic and real data.
