Apache JMeter Reviews

Apache JMeter's key feature is its ability to manage load profiles, gradually increasing requests over time. This was crucial for us as we tested our application, handling unique protocols and increasing load steadily. JMeter helped identify bottlenecks by measuring response times as we increased request flow rates. This data guided us in optimizing our system's performance and scaling hardware when needed. Recently, new tools like Platinum Consultant have emerged, but I haven't explored them thoroughly. My colleagues prefer these newer tools over JMeter.

JMeter helps us track response times between request and response. As we increase our workload, response times also rise, indicating potential bottlenecks. We use JMeter to gauge when we need to upgrade hardware or optimize our application for better performance. It's effective in measuring various request types and their corresponding response times, making it a valuable tool for assessing system performance.

I appreciate JMeter's simplicity and power for performance testing. While I haven't used all its features, the ability to simulate heavy loads from multiple users is quite beneficial. However, in my current configuration, we haven't utilized this specific aspect of JMeter. Compared to other costly tools like Hewlett Packard, JMeter is free and easier to use, although there are newer tools like Gatling that I haven't tried. Overall, JMeter is simple and effective for performance testing.     

Improving JMeter's sync time could be beneficial. For example, compared to a Hewlett Packard tool that required four machines for load generation, JMeter reduced this to possibly just two machines for the same workload.

I've been a junior with a few years of experience using Apache JMeter for load testing. It's a straightforward tool with useful features, although not entirely unique. 

Scalability is near-linear, especially with custom configurations.

Setting up JMeter is straightforward, not complex at all. Deployment time depends on the code you write for JMeter, which is executed efficiently.I've used it on-premises, but it might also work in a cloud configuration

Since it's free, there's no need for extensive support or improvements in pricing.

Overall, I'd give JMeter a solid ten for its simplicity and effectiveness in typical tasks. While the UI could be slightly better, it's not a critical issue. JMeter provides valuable data and insights through its graphs, and its main benefit lies in being free, simple to use, and widely recognized.

I've been using JMeter mainly for performance testing and some repair testing as well.

The solution is open source, so we don't have to pay for anything. That is a good thing since we can save the licensing costs, et cetera, as an organization. If you go for an expensive tool like LoadRunner or even Loyalty or Locust, you'll have to spend from your budget. JMeter has everything we need without the cost.

It's a powerful tool that is open source. There are various functionalities that can be used in various combinations. You can use Jmeter for automation, like getting some APIs. You can use JMeter for the performance testing. You can add listeners. You can look at the results and can generate a load with JMeter. The beauty of JMeter is there is a lot of support from the communities online who have worked on JMeter and can give first-hand advice. Most of our queries are already answered by someone, so we get the benefit of learning from them. 

It's a good tool for automated performance testing and some behavioral things.

It has a lot of customizable features. There are a lot of open libraries that you can download, and each time when you go for a new requirement, you will get new libraries. 

The setup is pretty easy.

The only thing is the learning curve. It's high.

We'd like to see more third-party integrations that can be handled quickly.

Support-wise, while the community is strong, it would be nice to have the option to reach out directly to JMeter. 

For performance testing, you need to correlate, et cetera, so we have to do it manually in order to get the right to regular expressions.

I've been using the solution for five years. 

As an open-source tool, when changes happen, it may be a bit unstable. This is occasional, and for the most part, it is fine. I'd rate it seven out of ten in terms of stability. 

The solution is scalable. I'd rate it ten out of ten.

While there isn't any traditional support, there is a very strong community around the solution. There are so many people using it and contributing to solving problems, you can easily find answers to your queries online.

The solution is straightforward to set up. I'd rate it five out of ten. There is a bit of a learning curve at first, however, once you start using it and taking advantage of its capabilities, I'd rate it nine out of ten. 

In the areas where we do some prototyping and also some areas where we want to save money and not focus on the revenue, we use JMeter. It's a very powerful tool. 

This is an open-source solution and is, therefore, free to use. 

I'm a customer and end-user.

I'm not sure which version of the solution I'm using. It's not the latest, however. It may be about one year old. 

You can deploy both on-premises and on the cloud. 

Once you go ahead and implement JMeter and you learn the process, it's a great tool. It could be a great asset for any organization as it is a highly customizable tool. If you can handle the learning curve, it will be worth it. Plus, as an open-source tool, you can save a lot of money on licensing. 

I'd rate the solution eight out of ten. 

When I was last using JMeter, we were simulating 200 concurrent users and evaluating performance based on transaction times. We were defining SLAs based on the results.

Essentially, we created load scenarios and testing different ones using different workload models.

The recording and playback functionality is helpful.

The reporting is not very good.

When we run with multiple users, it takes a lot of memory.

With respect to the recording and playback functionality, the auto-correlation parameterization is not easy and should be improved.

I have been using Apache JMeter for about four years.

There are issues with stability when running with multiple users because it consumes a lot of memory.

Scalability is fine, although it is important to remember that JMeter doesn't run on its own. It needs to work with load-generations such as BlazeMeter. LoadRunner is the same in that you need a cloud-based infrastructure to run it.

There is no official support. There is a forum where you can ask questions and they respond to you, but the technical support that we have with LoadRunner or NeoLoad is not available.

I have used many similar solutions in the past such as New Relic, AppDynamics, NeoLoad, and Micro Focus LoadRunner Enterprise.

JMeter is not as good as LoadRunner or NeoLoad, and it isn't as easy to use, but it's okay because there is no cost. LoadRunner is too expensive, in my opinion. NeoLoad is cheaper, although not significantly.

From what I have seen, many companies are adopting JMeter because it's free. Especially in Canada, using JMeter seems to be the new trend. Some companies are choosing NeoLoad over LoadRunner because it is easier, faster, and cheaper. Whatever they need to do can be completed quicker. The main problem with NeoLoad is that obtaining resources is harder.

Given all of the choices, my preference would be to implement NeoLoad.

The initial setup is straightforward. I would not say that it is complex and if you already have the file downloaded then it will only take about half an hour to deploy.

I took care of the deployment myself.

I was using the free version of the software.

My advice for anybody who is considering JMeter is to just install it and try it. Creating scripts is a different process when you compare it to LoadRunner or Neoload. There is different terminology compare to these two products, so if somebody has not used JMeter then it may seem difficult at first.

I would rate this solution a six out of ten.

We use this solution to load test functional behavior, and measure performance.

We really appreciate that the solution comes with a live community, which continuously provided plugins and support protocols.

We would like some reporting and analysis tools to be added to this solution.

We would also like the manual available for this solution to allow for better usability; it can be quite complex for new users, and the product is not always very intuitive. 

We have been working with this solution for 12 years.

We have found this solution to be a stable and reliable tool.

This solution is easily scalable, you can distribute the larger generation among several machines in the LAN, or you can use the cloud variation of the product.

This solution doesn't come with technical support, but there is plug-in wide community support, where organizations can ask questions about issues they are experiencing.

This solution isn't actually deployed, it is a zip file, which is extracted. It can also be deployed via public cloud, if an organization chooses the cloud-based model.

This is an open-source solution, so there are no licensing costs involved.

We would recommend that organizations considering this solution invest time in research of the product before implementing it. There are a lot of online resources that can assist with this, so the business can check if the solution will meet their requirements.

I would rate this solution an eight out of ten.

We use Apache JMeter for load testing, where we provide the throughput time. Apache JMeter allows me to give any number of users to put the load in a particular time frame. With Apache JMeter, we won't need multiple tools with the application or to give a load for the application.

Apache JMeter's UI can be made more colorful.

I have been using Apache JMeter for two years.

I rate Apache JMeter ten out of ten for stability.

Around 10 people are using the solution in my team.

I rate Apache JMeter a nine out of ten for scalability.

Apache JMeter's initial setup is easy.

Apache JMeter's deployment takes half an hour to one hour.

Apache JMeter is a free, open-source solution.

I recommend users explore each and every functionality of Apache JMeter.

Overall, I rate Apache JMeter a nine out of ten.

We use JMeter for performance testing. Our testing team has 50 to 60 people.

JMeter lets us generate virtual users and T-load, per our requirements. It's easy to configure and adjusting the virtual users according to the DPS we want to achieve.

It should be easier to combine multiple scripts. If you have multiple scripts, you need to write a new script to combine those scripts. The virtual user generator is slow.

We've been using JMeter for six months.

With an on-premises deployment, we run into some performance problems when we have a high load. It's not that stable if we increase the scripts or the load. But that could be something in our environment.

JMeter is an on-premise solution, so it has limited scalability. We are looking for a cloud-based solution that is scalable and elastic. 

I rate JMeter six out of 10.

We are in the financial industry in India and carry out performance testing. We deal with  SWIFT messages and financial messaging systems. A few years ago we had 2 million transactions in five hours; today it's 2 million in two hours. To measure these performances, I use JMeter for regression. We have Exadata, Exalogic infrastructure. We are users of JMeter and I'm a technical specialist. 

This tool is very user-friendly and easy to use. It's open-source so there are no costs involved for the non-production environments. It's easily available to anyone who wants to use it and it has all the features required for performance metrics.

I think it has some proxy-based dependencies which require specific proxies to be set up or disabled, which causes problems when we are working in certain specific environments that have a proxy setup. When we want it to do a record with some new scripts, there are some challenges there.

I've been using this solution for two years. 

The solution is stable and easily scalable. 

The support is very good, with good technical teams. Whenever we get stuck they support us and provide solutions. 

The initial setup took only 10 minutes but there were some complications with the product initially having less features. That has been greatly improved. It's easy to do maintenance of the test tools which we develop, and it's easy to maintain as a product. We have around 20 users of this solution. 

It's open-source, so there's no cost. If you need some support from the vendors there will be a charge for that. 

I would recommend this solution. Most of the support, guides, and tutorials are available on YouTube. 

I rate this solution an eight out of 10. 

We engage in performance testing using JMeter based on the client's requirements. We decide the endpoints for JMeter based on the domain and application requirements. The requirements, like 50 users per minute or 500 users per hour, guide our performance testing framework.

JMeter has allowed us to effectively verify that, based on pre-requirements, performance standards are met. Since it's an open-source tool, it also allows us to reduce the expenditure on performance testing tools.

The different listeners in JMeter provide various reports and results. It's very useful for performance and load testing. Its compatibility with external tools, such as the ability to import scripts from Selenium and Azure DevOps, makes it a robust and flexible option.

I would recommend the inclusion of plugins for AI in JMeter. Some features still require a certain knowledge level to use effectively, and making these features more user-friendly would be beneficial.

I have not been a direct team member but have managed a team working on JMeter for almost eleven years. In my nineteen years of experience, I have engaged with performance testing, with JMeter being part of our toolkit.

Stability is not a concern for expert users of JMeter. However, stability can be an issue for beginners.

JMeter is widely used and very scalable, rated between eight and nine in terms of scalability. It can also integrate with cloud solutions like Microsoft Azure.

There are many online blogs, forums, and video tutorials available for JMeter, providing substantial support for both beginner and intermediate levels.

Positive

LambdaTest and BrowserStack were part of our working user experience, but not extensively more than that. I initially worked with other performance testing tools like LoadRunner.

The setup for JMeter is very easy. There is no installation required; it is simply a package that needs to be imported and can be set up within half an hour or less, depending on the download speed.

Our clients cover the necessary licensing costs, particularly when using cloud services like Microsoft Azure.

JMeter itself is an open-source tool, so there are no licensing costs associated when running on-premises. Client-covered SaaS licensing, such as with Microsoft Azure, does not involve any costs on our side.

It's important to be very skilled in manual testing concepts before starting with performance testing. Due to JMeter's advanced level of techniques and skill requirements, extensive hands-on experience with real-time projects is needed. It generally takes three to four years of practical experience to master.

I'd rate the solution eight out of ten.