Apache JMeter Reviews

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. 

The use cases are mainly for performance testing and for test case management of the different APIs.

Initially, we didn't have any tool for performance testing, particularly open source. JMeter, since it is open source, we can test our APIs pretty quickly and we can work with different teams to provide performance testing very quickly. It doesn't take up much of our time.

The ease of scripting is great. 

The modular design is very useful.

It is easy to set up.

The solution is stable.

It can scale well. 

If JMeter could provide a web version of editing, that would be good. 

If JMeter can provide its own cloud version rather than depending on BlazeMeter, the commercial version of JMeter, that would be ideal. If we could have somebody right on the front end of JMeter, using it on any of the clouds, including AWS, GCP, or Azure, that would be very helpful. it would be better than me going for using commercial services.

I would like to have some kind of cloud version that can be implemented. Or we would like a Docker version. A Docker version is something that I would look for.

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

It is a stable, reliable product. There are no bugs or glitched. It doesn't crash or freeze.

The solution has been scalable. 

We have almost 100 users on the solution. 

We likely won't increase usage in the future.

I do have some knowledge of technical support. 

This is an open-source tool. If I write any issue in the forums, somebody will answer it pretty quickly. The open source technical support they have on offer is good.

We did use a different solution previously. 

Most people know JMeter more than the other tools. It's easy to learn and quick to execute. It's also open source. You can get a lot of solutions across the internet. If you are having some issue or error, somebody or the other may have faced that same issue, and he may have found out the solution. It makes troubleshooting easy, having crowdsourced troubleshooting. That was a factor in our decision-making. 

The initial setup is not straightforward. It's simple and not complex at all. 

We only need two people to maintain the product. It doesn't take a lot of staff. 

We have our own in-house team that can handle the setup. 

We've definitely seen an ROI. 

We use an open-source version of the product. However, there are cloud services that we use. I'm not sure of the cost of the cloud services.

We looked into Micro Focus and Cavisson NetStorm. However, they were licensed tools, and we decided against them. 

We are using the latest version of the solution. 

We are using a cloud version of JMeter that is called BlazeMeter.

If you are a company that is evaluating other licensed tools, just go for JMeter. It's open source, easy to use, and the most widely used across platforms. It would be much simpler than using the other licensed tools. Other licensed tools may have pretty good technical support. However, most problems with JMeter can be solved using the solutions that are available on the internet.

I'd rate the solution eight out of ten.

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. 

The primary use case for the solution is to test web applications.

The most valuable feature is that the solution is open source.

There are a lot of areas in this solution that can use improvement. The solution is not user-friendly, there is no framework for autocorrelation or parameterization.

I have been using the solution for a little over one year.

The new version of the solution is stable.

The initial setup is straightforward as long as you do not require an advanced setup, which can be difficult. The basic setup takes only one hour.

The solution is open-source.

I give the solution

The only support available for the solution is online because it is open-source and does not come with technical support.

To anyone that is thinking of using the solution, I suggest you familiarize yourself with regular expression.

I am using JMeter only to test some web services.

You can moderate some transactions which aren't available to too many users. You can use JMeter and compress as needed or to support as many users as possible. 

I am a basic user. I couldn't explain the different features deeply. I use, for example, the web services. I like the features where you are programming at an increased rate in web services. I use those features. For example, as part of using our web services, if there are 100 transactions with three threads, and I want to finish with 5,000 transactions with 20 threads on different pages, I can find the rate which my server used on each page. I like this feature in JMeter.

It's easy to set up.

Apache should have a graphic interface. That would help beginner users a lot. Sometimes it's hard to do what you need to do via the command line. 

I've been using the solution for around two or three years. 

The solution is stable. There are no bugs or glitches, and it doesn't crash or freeze.

The solution can scale. However, it requires configuration to do so. I don't have much knowledge in regards to how to scale exactly.

On the other hand, if you have a cloud server with 10 servers and you are using the same DNS for all servers, as all servers are working with the same application, and you have for example a load balancer that provides balancing to each one of these ten servers, I am not sure if Apache JMeter will report the different servers separately. I imagine not.

Different implementations of JMeter Runtime could be used to point to each one of these 10 servers. You can use JMeter in different OS, for example, Windows, Linux, or Unix. You have a lot of features to use different instances with JMeter. However, this load balancer concept would be harder to explain.

Right now, we have around two or three guys working directly with the product.

We are evaluating automatization apps currently. We are using Jenkins, and I am sure we will start with JMeter later. However, I have not defined a roadmap to expanding usage of this product just yet.

I have not used technical support.

I have used some other solution previously. However, I cannot recall the name. It was likely SoapUI. We picked up JMeter as it is free to start with and easy to pick up.

The product is simple to set up. 

For example, you can just support Apache JMeter with the Java installer feature, which downloads the JDK or Java Runtime from the Oracle pages, for example. Or you can add the Runtime as a part of your installer, and after the installation, have a common user in Windows, for example, as an option. There is some knowledge of Java needed, and you do need to use the command line. Some may feel a bit lost when they start. However, there are different ways to do it according to your comfort level. 

It should have something for the front-end user to help them prepare the environment correctly, however.

We have two to three people handling the maintenance of the product at this time. 

I have not really noticed a return on investment. 

I cannot recall the exact version number we are using. I always download the latest. 

We are currently using our own servers to provide the network.

I recommend JMeter if your goal is to design some stress tests. JMeter has some features. For example, you can start with tests on the command line. You can join instantly on our current deployment batches. Jenkins has some support for JMeter as well. On another hand, you can make a simple bridge to start the JMeter process with the command line in the same Jenkins deployment. You have a lot of features on hand.

I'd rate the solution eight out of ten.

Our primary use case for the solution is comprehensive performance testing. It measures how our applications are doing overall with a lot of users. For example, if we want to simulate 100 users doing transactions simultaneously, we want to see if our app handles it well and how fast it responds. In addition, we can utilize the solution to identify time spent on operations.

We find the ease of use and the reports and graphs available valuable.

The solution needs more metrics for reporting.

We have been using the solution for two years.

The solution is stable, and we have not had any issues.

The solution is scalable, but I cannot comment on the extent of its scalability because we have yet to scale widely.

We have not had experience with customer service and support.

The initial setup is straightforward.

We use the tool as an open-source tool, so we do not pay for it.

We chose this solution because of its affordable cost, ease of use, and popularity.

I rate the solution a nine out of ten. I advise users considering this solution to take a course to get familiar with it quickly.

We've been using Apache JMeter for load testing, spike testing, and endurance testing. We use the solution mostly for nonfunctional use cases, except for the security aspects, because those aspects require a different tool altogether.

What I like best about Apache JMeter is its user-friendly GUI because even if you don't have very good coding knowledge or understanding, or even if you don't come from a development background, you can still use the solution with just a few clicks. This is what's unique about Apache JMeter, in comparison with other tools in the market.

As Apache JMeter is open source, when there's a missing feature, you can search in several community blogs for plugins that you can use to modify Apache JMeter to meet your requirements, and this is another advantage.

What needs improvement in Apache JMeter is the very high load requirements when you want to scale it beyond certain thresholds. For example, small to mid-range testing is very easily done with Apache JMeter, but if you scale and increase the load, then it would be a problem because the tool consumes a lot of resources, probably because Apache JMeter provides an enriched UI experience, so it consumes a lot of memory and requires high CPU usage. This means you have to manage your infrastructure, or else you'll have high overhead expenses.

As Apache JMeter is a heavyweight tool, that is an area for improvement, though I'm unsure if Apache can do something about it because it could be a result of the way it's architected.

What I'd like to see from Apache JMeter in the future is for it to transition to the cloud, as a lot of cloud technologies emerge around the globe, and a lot of people prefer cloud-based solutions or cloud-native tools. Even if a company has a legacy system, it's still possible to transition to the cloud. I've worked with a company that was an on-premise company that moved to the cloud and became cloud-native. If Apache JMeter could transition to the cloud, similar to k6, then it could help lessen the intense resource consumption that's currently happening in Apache JMeter.

I've been using Apache JMeter since 2020, so it's been two years since I started using it.

Apache JMeter is a stable product overall. A very large community in the software industry uses Apache JMeter, and though it's open source and there's a continuous phase of improvement going on with it, it has stable versions available for my company to continue testing it.

Apache JMeter is scalable in the sense that there's a master/slave architecture available for it where I can scale as many slaves along the way, but when a huge number of users is required in a particular load test, and you have to scale a lot beyond a particular threshold, the resource consumption becomes too high and requires considerable overhead. Apache JMeter consumes a lot of memory, and that's a hurdle, but it's scalable up to a certain point. If a very, very large organization requires very heavy load testing to be done, it would be better for that organization to go with some other tool.

Because Apache JMeter is an open-source tool, you get support from the community. The challenge with open-source tools is that if there isn't enough community, then the support and development you get would be limited, but as Apache JMeter is widely used, the community is vast and the support is sound. Unlike with Micro Focus LoadRunner, when you encounter an issue, you can report that to Micro Focus and the Micro Focus team will take care of your issue. It doesn't work that way with open-source solutions.

For the support I get from the community, on a scale of one to five, I'm rating it a three because there could be instances where you could not get a resolution for your issue. After all, Apache JMeter is a free product, so you can only rely on community support. Though the community for the tool is so big and Apache JMeter is widely used, and there'd be a lesser amount of circumstances where the solution for your issue isn't available yet, there could be between one percent to five percent chance of it happening, so that could be troublesome.

The initial setup for Apache JMeter is pretty simple. There isn't much dependency, in general. For example, in macOS, you can just download the tar files entirely and just untar the files. There's no installation of specific extensions required. That's for macOS. For Windows, there would be .exe files. From that perspective, setting up Apache JMeter is quite easy. You can just run it locally, untarring it in any particular location. Just one setup that's required to be done is setting the Java home path to start the app. Otherwise, it's pretty straightforward and very quick to set up.

On a scale of one to five, I'm rating the initial setup a four because there's always some room for improvement.

Apache JMeter is an open-source solution, so it's free to use.

I evaluated k6 and Locust.

I'm using Apache JMeter for work. Locust is also used within the company, as well as k6, but I only touched base on those solutions.

The projects I'm working on currently use Apache JMeter, but my company works across regions and uses different tools, including Gatling and Locust.

Apache JMeter is used daily, for the range of projects I've been testing it on. A new government project came in, and I chose Apache JMeter for it because of its simplicity and user-friendly interface.

My rating for Apache JMeter is seven out of ten.

We use this solution for functional API testing, and performance testing.

This solution allows us to test all the functional APIs through it, then record and run the APIs.

This solution is easier to use than any other tool in the market; there is not even a requirement to learn a lot of scripting in order to use it.

We also appreciate that the solution is open source, so it has a very big community to utilize if we need help with an issue.

At present, if the number of virtual users increases beyond 10,000 when testing, then it results in a Java heap which causes the solution to crash.

I have been working with this solution for around seven years.

The stability of this product is good, outside of the issues with adding virtual users during testing.

This solution is scalable, but only up to a certain point when adding virtual users, before performance issues begin to occur.

The initial setup of this solution was quite straightforward, and deployment only took one to two minutes.

We implemented this solution using our in-house team.

This is an open-source solution, so there are no licensing costs associated with it.

We would recommend this solution to any QA or developer as a 'must-try product'.

I would rate this solution an eight out of ten.