Apache JMeter Reviews

Apache JMeter is quite flexible and it is also well distributed. It is quite flexible compared to Micro Focus LoadRunner.

JMeter is easy to script. There is less of a problem with doing correlations and parameterization. 

It is not something that can be compared with Micro Focus LoadRunner. It gives the facility too easily; you do things through UI. With JMeter, you really do not have any easy UI to work as, like a Micro Focus LoadRunner.

The stability could be a bit better.

Compared to LoadRunner, it hasn't any proper UI. Recording the script is also not flexible in JMeter. In LoadRunner, we have a couple of options, such as URL-based recording and HTML-based recording. In JMeter, it's not like that. JMeter has a recorder, however, it is not easy to use. It is a bit tricky to configure the automatic recording in JMeter. 

I've been using the solution for four or five years. 

JMeter, stability-wise, is good, however, it is being developed by the community. Therefore, stability is always an open question there.

The solution can scale a bit. It is scalable, however, not like LoadRunner. I have not tested it as such yet. I'm not sure about how fully scalable it is. 

I'm also familiar with Micro Focus LoadRunner.

The implementation process is not so easy. It's difficult to configure.

I'd rate the solution a seven out of ten.

I'm an end-user and a customer. 

I consider Apache JMeter to be a fundamental tool in the industry for performance testing. Its primary advantage lies in being free, making it accessible to everyone. The platform boasts a wide range of plugins, regularly updated, and has a substantial community. You can find information on almost any topic in the community forums or Q&A sites related to code.

Apache JMeter is well-known and widely used among developers, particularly on popular developer forums. While it may not have the most user-friendly interface, it offers strong support through official manuals and various articles from companies providing load testing services. 

The tool is free, has a substantial community, and serves as a fundamental choice for testers, especially those new to performance testing. While other tools like K6 may be more developer-oriented, JMeter's affordability and accessibility make it suitable for those without extensive performance testing experience.

Given that Apache JMeter is a free and open-source tool, documentation improvement may not be a major concern, as it is mostly contributed on a voluntary basis. The essential information is already available. However, in terms of the interface, there are occasional bugs, and the tool may not address them as quickly as some users would like. Fixing defects and bugs might take a considerable amount of time, with users sometimes having to wait for several months or even a year for the next release to address specific issues.

I have worked with Apache JMeter for years. 

In terms of stability, there have been some instances of unknown bugs, but these are documented on the official pages and tracked in bug repositories where users can find descriptions and potential workarounds. Users with less experience may encounter unexpected behavior, but with online resources, such as Google, they can understand and address the issues. Some known problems, like internal loop issues when launching from the MacOS terminal, can affect stability, but they are not critical and usually have workarounds. While these issues may slightly impact the user experience, they do not significantly detract from it. On a scale of ten, the overall user experience with JMeter might be rated around seven or eight.

Scalability is possible for both small and large companies. In smaller companies, JMeter can be scaled across multiple machines, utilizing them as load generators. For more complex network setups, collaboration with the DevOps or system administration teams may be required to handle firewall configurations. In large enterprises, options like Docker Swarm or Kubernetes can be employed. Additionally, using JMeter images or containers within these frameworks allows for quick scalability.

While I haven't personally engaged in direct interaction with support, I have encountered challenges and utilized forums and official support channels to address and resolve those issues. So, yes, I've had experiences leveraging these resources for problem-solving.

A few years ago, I found Apache JMeter to be a reliable tool, and while it may have changed since then, I haven't used it recently for a direct comparison. Around five years ago, I had a positive experience with Neotys, which was an excellent tool, albeit expensive. However, as its pricing is now contact-based, I'm not sure about the current costs. Additionally, I've recently explored K6, which seems promising. K6 is actively developed and evolving rapidly. It caters more to a coding-centric experience, making it favorable for developers who appreciate JavaScript-based coding without extensive installations. This tool might see significant growth in functionality in the coming years.

If someone is completely new to Apache JMeter, it might take around one hour to half an hour to set it up initially. This includes spending time reading manuals, watching YouTube videos, and getting familiar with the tool. For those with some experience, the setup process could take as little as ten minutes. This involves downloading and installing JMeter, configuring Java if necessary, and adjusting path variables. The overall time may vary based on the machine's readiness and the user's familiarity with the setup process.

One piece of advice I often provide to those venturing into performance testing with Apache JMeter is to carefully consider the expected load. Due to its utilization of the Java Virtual Machine, JMeter can be memory-intensive. For extensive testing scenarios with a high volume of virtual users and transactions, it's crucial to meticulously configure JMeter, considering each element in the scenario. However, for simpler yet intensive testing needs, individuals might find less resource-intensive tools like Gatling or Locust more suitable.

If it were a commercial tool, I'd rate it an eight, but given that it's a free and non-commercial tool, I'd lean more towards a nine. While it's not perfect, I believe it's one of the best options available for now.

Apache JMeter is utilized for load testing of applications such as APIs and web services. Various types of load testing can be conducted, including stress tests and load tests. It supports different types of protocols, such as HTTP, HTTPS, SFTP, and others.

The most valuable features of Apache JMeter are user-friendliness, large resource, and the quality of assistance they provide. Additionally, it is easy to integrate with cloud platforms, such as AWS.

Apache JMeter could use improvement in reporting. Currently, it isn't easy to generate reports in PDF format. While receiving reports in PDF format is possible, it requires a lot of customization. Additionally, when comparing the load test to others solutions it could improve.

I have been using Apache JMeter for approximately five years.

Apache JMeter is a stable solution.

We have more than 100 people using Apache JMeter in my organization.

We have multiple clients using this solution and all of our testers are using the solution.

My advice to others is for them to go through online tutorials before using the solution. It is easy to use, and anyone can quickly learn and test their application.

I rate the scalability of Apache JMeter an eight out of ten.

I have not contacted technical support.

The initial setup of Apache JMeter is easy and simple to configure. The whole process of implementation takes approximately half an hour. The first step is to download Java and install it. The last step is to download Apache JMeter and install it. 

The main reason we chose Apache JMeter is that it is cost-effective and easy to use. There is no need to pay for additional services. Additionally, it does not require additional payment to vendors. The solution is open-source and free.

I rate Apache JMeter a nine out of ten.

We primarily use the solution to manage our capabilities. Wherever the business goes, we need to work within the expected benchmark. In terms of the user bases we deal with, most of these are products from different locations with different types of functional flow-out. There are environmental integrations also running in the background, which a user is basically accessing while going through a particular workflow. 

We'll also handle the reporting section of our data management responsibilities utilizing this system.

The reports and analysis tools are very good. They are the solution's most valuable features.

The GUI could be improved. When we go into GUI mode, there are occasions where it will not sync with our expectations. There are crashes that happen that will stop the solution from performing. It seems we get minor glitches when we go into GUI mode.  

The data client architecture that we have isn't so great. If we are to consume the data, it won't clear because there is tech running on different agents. 

When I need to pull the reports from different agents, it's not user-friendly. The reporting can be difficult to handle. It's hard to increase it if you are working on a client's architecture.

It's not easy to get the data from one place or to do customizations. 

There are other solutions that allow users to model their load and structure with them. You can't do that on JMeter. 

On other solutions, like Silk Performer, you can do network packeting, which you can't do on JMeter. They should add this to the solution as a capability in the future.

The support management needs improvement. Support is coming from consultants; you will not be able to get on-premise support from all of their agents in one place. On Silk Performer, for example,  they have the capability where you can basically have a summarized report from different agents.

Personally I've been using the solution for the last 10 years. However, in the program we are in, I've only been using this tool for six months.

If you want stability, you will have trouble, because the system is not uniform. You have to do a lot of modeling. 

If you're talking about mobile platforms, JMeter will not allow you to capture the performance of applications on your mobile platform. It's an area where the solution is lacking. It doesn't have the capability to allow developers to check the performance on an AP app.

You can scale the solution, but you will run into issues if you want to run, say, 1,000 users.  You will have to configure multiple agents and then distribute your load. It's quite difficult to manage everything on a single agent.

The initial setup is straightforward. We found it quite easy. For us, it wasn't complex at all. The solution is up and running quite quickly and doesn't take long at all to set up and deploy.

We've looked at Silk Impact and Load Balancer in the past. Each of these solutions offers a few different functionalities that aren't necessarily available on JMeter. For example, on both, there are more network features available that aren't included in JMeter and you can model your load and structure with them as well.

If companies have mobile development, they should use JMeter. If they want to integrate it with the PA pipeline, JMeter will work well. However, there are other platforms and solutions as well.

Other options include Silk Performer and Load Impact. These two solutions have other capabilities that JMeter doesn't have. You can basically model your load and structure with them. You can't do that on this solution. On Silk Performer, you can also do network packeting, which you can't do on JMeter.

Then there are some network features available in Load Impact as well as Silk Performer that aren't in JMeter. 

I'd rate the solution eight out of ten. The solution has certain limitations, but it's still a good product. 

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.

We primarily use the solution for performance and delivery testing.

It's a free tool. It's a very common tool. There's a lot of support in the community for this. It mainly supports web API testing.

The UI could be better. It can have some Reach UI also, which would be helpful, and maybe a relatively simpler way of using it. It needs simple modules. There are quite a lot of things which are kind of abandoned, so they can definitely improve on it.

Integration with some of the other features should be managed. However, it's open source, so there is not much to complain about there.

It's an open-source tool; we cannot ask for additional features really.

The product could use some kind of filtering and monitoring and different degree of dashboards and analysis. If that can be provided, that would be very, very helpful.

I’ve used the solution since 2009.

The solution is relatively stable. There are no bugs or glitches, and it doesn’t crash o freeze. It’s reliable.

It can scale. However, what others say about scalability is that you need to have some proper calculations to be done first.

We have dealt with support. Technical support is found in more technical forums. It’s open-source, and communes are where you go for information. We have received good responses when we have inquiries. There are quite a lot of forums in general available.

Now, as we have grown as an organization or as a team, there are still questions such as, "What are the limitations of this tool?" And we put that to JMeter so we can learn what is best for the maintenance.

The installation can be a bit complex. There are quite a lot of things and issues if you go deep into it and if you're setting up JMeter. For example, direct script captioning is slightly different. It's a bit more complex, the correlation parametrization. Setting up the workload model can be complex as it is based on a Java service mechanism.

It becomes a bit challenging to manage. If I want to put a 50,000 user load, I have to be very careful how the memory is utilized. I must be very aware of the underlying system's capability to execute this. I have to make it into multiple nodes and run them in parallel. There are some calculations, and there are some good power processes that will be required when you are using JMeter. You need to understand its limitations and load work them on.

The solution doesn’t really need maintenance. They're open-source tools, so we don't expect any maintenance. What we typically do is we pick up a particular version and understand the limitations of it. We then play within those limitations.

We handled the initial setup in-house. I handled the setup myself.

The solution is free to use.

We may be using the latest version. I don’t know the exact version number.

It is on-prem. However, we can put it on the cloud as well. We install it on any machine, so it can be a local or cloud-based machine.

I’d recommend JMeter. One critical piece of advice is to plan properly. For JMeter, planning and having an understanding of the limitations are important. If you play within those limitations, it is a really great tool. There are trade rules that apply to a lot of things that we use. However, there's plenty of material available so far. Whoever is doing it, can plan it accordingly. They can create those tests, and execute those tests. That said, at the same time, be aware of the scalability of the JMeter. For example, a single JMeter line, which is running, can take 1,000 to 2,000 threats, not more than that. Again, it depends on the available hardware. If you want to scale to, say, one million or something, different parts of planning are needed.

I’d rate the solution eight out of ten.

I've used JMeter in conjunction with Selenium, Java, and Log4j for logging. I used it before
I ended that contract in August. Its version was up to date at that time.

It was used for an e-commerce site that is specialized in C-PAP or weaving machines in effect. Their max was a thousand people logged in at once. I, of course, pushed the boundaries on that, but it was to test the performance of the website, and of course, I'm had to try subsystems, database interactions, etc.

I'm a total geek, so I liked the fact that I got to program. The biggest thing I liked about it is that there is a huge user base out there, and being shareware and being Apache, if I have any question on how to get something done, I get 18 different answers. Out of those, there would be at least a few good approaches for what I was trying to do. So, the support system out there is most valuable.

I sometimes found the documentation to be not as explanatory as I would've liked it. In the cases that I can think of, I was looking for a rather hand-holding approach with Step A, B, and C, but then I realized that with a product that is open source like this, you can't do handholding. That is because there are so many different uses and different unique environments and setups for it, but I remember thinking a few times that if they only just said this.

If I were going to be Mr. Selfish and say anything I want, I'd say a full feature GUI that lets me drag and drop different modules in line. It could have a simple-to-use GUI.

I have been using this solution for probably a year and a half.

I didn't have any issues with the stability of JMeter itself. There were definitely issues with the program I was testing, but that's why I was testing it.

It was very easy to scale, but I was barely scratching the surface. I have spent 17 years at Microsoft, and for the performance testing that we did there, we had 8.3 million users at once, as opposed to a maximum of a thousand. If I'm scaling, I have to do it quite straightforward and simple, but it was very minimal.

Only I was using it. It was the QA department. I showed it to some of the devs, and they were very interested. A couple of them tried it, but none were actually using it day-to-day for testing out the environment.

I would rate them an eight out of 10 because sometimes, they would take two or three days to get back to me. Of course, at that point, you're like, "I need the answer; I need to answer." So, it was a little bit unrealistic in terms of expectations.

At that particular company, I was the one who was tasked with coming up with the solution, so that was the only one that I looked at simply because JMeter is industry standard, but at Microsoft, they wrote their own custom tools, so I used custom Microsoft tools.

It was rather complex. It is a complex product, but that part of it was very well-documented. I didn't have any problems with it.

Don't be shy in asking questions. Google/Bing is your friend. It is complicated. There's no reason to spend eight hours trying to figure out something, except unless you are trying to learn in-depth. There are a lot of people who've done exactly what you're trying to do, and it doesn't matter what it is.

I would rate it a 10 out of 10 because it is industry standard. It did everything I could've asked. I barely scratched the surface, but what I needed it for, it did well and in a very straightforward-to-implement way.

Any front-end technologies like Angular, React, or others might access the services. Therefore, you must ensure that using SAP with JMeter works fine. Unless you ensure this, the front-end team may not access the services properly.

You can save the state of your tests and test plans after conducting tests, allowing you to showcase the results to others later. This feature makes it easier to demonstrate what testing was done and share those test cases.

From an improvement perspective, consider a scenario where your application needs to retrieve data from PayPal and store it in an Excel file in an external network. Connecting to such a source using JMeter might take some time. Previously, you might have linked your application to a server to obtain these results. However, achieving this kind of integration directly in JMeter can be challenging. If it were possible to configure JMeter to handle such server connections seamlessly, its capabilities would greatly be enhanced.

I have been using Apache JMeter since 2004-05.

It is a stable tool and has been stable for a long time. Organizations have been using it extensively since 2017. However, it's important to note that while JMeter is excellent for testing the performance of your service, you cannot directly forward the results to the end user.

You can increase the testing scale. When deploying a microservice in a production environment, performance testing is essential. You should test to handle at least one million users, a minimum benchmark. 

From a developer’s perspective, if your service can handle one or two million users with a response time of less than one second, it is considered acceptable, provided the data is accurate. In production environments with multiple servers, response times might vary, but it is crucial to perform thorough testing in a local environment to ensure the system meets performance criteria. JMeter helps verify that the service can handle the expected load and deliver accurate results.

I am using Azure and GCP.

JMeter is easy to set up, taking about half an hour to install. However, the real effort lies in configuring and developing the tests, which can be time-consuming. 

If there is an update, it doesn't typically take long to come. They may release an upgrade within one or two years. If you have a test suite, it can be easily imported, and you can start using it. This process hardly takes more than half an hour.

Apache JMeter is configuring it properly, especially when dealing with SSL configurations. It can be tricky and time-consuming if you're unfamiliar with handling SSL certificates, keys, and JMX configuration. However, the process becomes straightforward if you know where and how to pass the necessary keys and configurations. Without this knowledge, you'll likely need to spend time researching and Googling how to set everything up. In contrast, if you're familiar with these configurations, setting them up in JMeter is quick and straightforward.

Overall, I rate the solution a nine out of ten.