Gatling Enterprise Reviews

My main use case for Gatling Enterprise is for performance testing of my microservices, and I find it easy to write load scenarios with minimal code. The reports generated are well written, featuring charts that help quickly identify issues. The charts and the reports are especially valuable for analysis as I can easily see response time, distribution, and error rates, which makes it easier to pinpoint where the system is slowing down. The initial setup was very fast and easy, thanks to the documentation.

I use Gatling Enterprise for performance tests of my microservices, validating system capacity against real-world traffic, and it helps identify bottlenecks swiftly. The generated reports make analysis easier, allowing quick insights into performance issues.

Day-to-day, I love the web-based reporting dashboard which is very crisp, clean, and highly intuitive. Navigating through response time, distribution graphs, percentile breakdowns, and transaction metrics requires zero setup, making test results immediately understandable for both technical engineers and management.

Gatling Enterprise has positively impacted my organization by simplifying performance and load testing, making it easier to create realistic user scenarios and execute tests at scale. It provides clear performance metrics and helps identify bottlenecks, response time issues, and system capacity limitations. This has made it easier for our team to validate application performance, detect issues early, and make data-driven improvements before production.

Identifying bottlenecks has improved, and we have been able to save time and make data-driven improvements before production.

We have been able to save three to four hours a day on performance testing and issue detection since using Gatling Enterprise.

The biggest benefit for me, and why I chose a five out of five, has been standardization across teams. We built a shared internal library of reusable load patterns, feeders, and helpers that any team can import. This means a new load test project can be up and running in minutes instead of days.

In my opinion, some of the best features Gatling Enterprise offers include the web-based reporting dashboard, seamless integration, intuitive UI/UX, being built on Akka and Netty, being open source, and having AI/Intelligence.

Regarding the AI or intelligence features, with the recent enhancements around automated test generation and smart reporting, creating complex simulation scenarios from HAR files or Open API definitions is faster than ever. This takes the guesswork out of script maintenance and also aids in anomaly detection in test runs. The seamless UI/UX, particularly the web-based reporting dashboard, is crisp, clean, and highly intuitive, making navigation easy for both technical engineers and management.

I love the seamless integrations into modern DevOps pipelines via native plugins for Jenkins, GitLab, CI, GitHub Actions, and Maven/Gradle.

Regarding Gatling Enterprise's AI capabilities, I think the security is very good. I specifically value the good security and governance capabilities provided by Gatling Enterprise, which include access controls, secure data handling, and the ability to manage sensitive information. However, I would like to see continued improvements in audit logging, transparency, and safeguards to ensure AI-generated outputs remain reliable and compliant.

Gatling Enterprise integrates well with our AWS environment, supporting performance testing for cloud-based applications.

The biggest limitation in Gatling Enterprise is distributed load testing. When trying to run distributed load tests, the issue arises because the open-source version offers no supported way to merge binary simulations and simulation logs from multiple nodes into a single consolidated report.

Support for the open-source version is community-driven only, and when you hit critical blockers, the official response is often that this is only supported in Gatling Enterprise.

I have been using Gatling Enterprise for the past four years.

Gatling Enterprise is very stable with minimum disruption and minimum downtime.

For scalability, Gatling Enterprise has been able to scale well for growing workloads and larger performance tests in my organization, supporting increased virtual users and complex test scenarios, although resource planning and configuration may be needed for optimal performance overall.

I have had a very positive experience with customer support, as they have been very proactive and supportive overall. I have been very happy and would rate the customer support a nine out of ten.

Previously, we relied on Apache JMeter for performance testing, and we considered Gatling Enterprise for its automation capabilities, code-based test scenarios, and improved integration with development workflows.

Gatling Enterprise was relatively easy to deploy with straightforward configuration, and the integration into our existing workflows was smooth. Some initial setup and tuning were required, but the overall deployment process was manageable. My experience with the configuration process was straightforward, with flexible options for customizing test scenarios.

Gatling Enterprise has helped improve testing efficiency by automating performance tests and identifying bottlenecks earlier in my organization. This has greatly reduced manual testing effort, saved developers time, and also helps prevent costly production issues.

The procurement process was relatively straightforward, with the main considerations being licensing, pricing, and selecting the right plan for our testing needs. The metering and billing experience was generally manageable, but clear usage tracking helped with cost planning. More detailed billing reports and greater transparency around usage-based costs would also be very beneficial. Gatling Enterprise pricing is reasonable for teams needing advanced performance testing. However, the licensing costs can be significant for larger teams like mine, which can be a bit expensive, but overall we are managing the price.

Before choosing Gatling Enterprise, we considered Apache JMeter and K6.

I would rate Gatling Enterprise a five out of five. Gatling Enterprise provides reliable performance testing results, but AI-generated insights should be validated against actual test data. I recommend Gatling Enterprise for teams that need scalable, automated performance testing. However, you should evaluate your testing requirements, licensing costs, and CI/CD integration needs first. Start with a small project and expand as your team becomes familiar with the platform.

My main use case for using Gatling Enterprise is for doing load testing, performance testing, or API level testing for a lot of the API endpoints in my back-end services here at Intuit. We use Gatling Enterprise for creating endpoints and then calling them and adding load, making sure our system scales properly.

We use Gatling Enterprise by defining the APIs inside Gatling. We create simulations and scenarios which are directly read by Gatling. In those scenarios, we define in the code what APIs we need to call. We then add load via the Gatling Enterprise user interface over a given amount of time by adding a number of users or requests for that particular scenario over a given time period. We then see how well our system is performing in that case.

The interesting thing about Gatling Enterprise is the fact that we can define scenarios wherein a particular scenario can have multiple API calls as a downstream happening in one scenario. This helps us load test a particular scenario or use case overall in depth. That really makes our system scalable.

The ability to add scenarios, the ability to configure concurrent users per second, and the ability to define how long a particular test should last are valuable features. After that, I can draw conclusive reports and graphs around how well the particular test took, how many API calls were successful versus how many errored out, how many were failing due to authentication errors, and what sort of granular errors I got. That really helps us understand the scale at which our system is performing.

I rely on the fact that we are able to add a particular number of users per second as simulations in the code or in Gatling Enterprise. The reason it is very important for my team is because it mimics the way actual users use our product in their day-to-day lives where there are periods wherein our system and product receive way more traffic, and that traffic results in way more downstream traffic, which Gatling Enterprise perfectly helps me capture.

It has led us to have really robust scalability testing, performance testing, and load testing, thereby making sure of our system integrity during crunch time or during times of peak traffic. It has helped build confidence in our systems.

We saw fewer outages and fewer periods of slowness in the product. Our number of customer complaints or customer escalations reduced by almost 20 to 30 percent over the period of a year when we initially started using Gatling Enterprise. As more and more teams are adopting this, the number is growing. It has led to real positive impact here.

The UI can be made a little better to understand. The overall user interface can be made so that non-technical people should be able to easily integrate with and understand what is happening in Gatling Enterprise. Additionally, there could be a really good AI integration in Gatling Enterprise, especially in the front end or UI part of it, wherein you should be able to describe a scenario in plain English, and the code should be able to automatically be generated.

I have used Gatling Enterprise for the last around five years, ever since I have been working with this company.

I have not experienced any stability issues with Gatling Enterprise.

Gatling Enterprise is pretty decent in terms of scalability. It scales well to all products and all services, and it is pretty uniformly implementable.

I have not needed to contact customer service.

It is definitely time and money saved in terms of user escalations and user actions occurring, but I am not able to speak on the exact details about it.

Before you start using Gatling Enterprise, please make sure to read all the documentation and then get up to speed with the UI because that is the biggest learning curve, but overall, it becomes smooth after that.

Gatling Enterprise is pretty decent. I have never needed to use customer support, but whenever needed, I find a good community online.

I gave this review a rating of 7 out of 10.

Gatling Enterprise is used by our organization to create performance test cases and functional test cases for our service. A specific example of one of the test cases we created using Gatling Enterprise is for a pricing service, which we built in Java, so we needed a Java-based testing service. Before we were using JMeter, but now we are moving to Gatling Enterprise.

Gatling Enterprise has positively impacted our organization by streamlining the workflow, easing the task, and reducing manual labor. In terms of hours saved, we have reduced approximately one to two weeks worth of work.

The best features Gatling Enterprise offers include being used in Java, providing a very good interface so we do not have to manually do the UI changes and can simply write the code. It is very much integrable with AI, and AI can write Gatling Enterprise scripts for us.

The AI integration has helped us significantly. We basically created a skill so that from the OpenAPI spec file, it can directly read the data and create the Gatling Enterprise script for us, so we do not have to manually code all the scripts.

Regarding Gatling Enterprise's AI capabilities, I believe it is pretty secure, and we did not find any issues working with it. Its accuracy and reliability of output seem pretty accurate and reliable, and we did not find any problems.

The setup is a little difficult. What I found is that you have to do a manual setup for Gatling Enterprise to be installed on your computer, and that can be improved.

I have been using Gatling Enterprise for approximately six months.

Gatling Enterprise is stable.

Gatling Enterprise's scalability is pretty scalable, and we did not find any issues.

The customer support for Gatling Enterprise is good.

We previously used JMeter, which was UI based and did not involve a lot of coding in it. However, as we are all developers here in Oracle, it is much easier for us to work with Gatling Enterprise.

The setup is a little difficult. What I found is that you have to do a manual setup for Gatling Enterprise to be installed on your computer, and that can be improved.

I have seen a return on investment. In testing, our team's employment situation has improved in that fewer employees are needed, and we do not need a large number of workforce as before when we were using JMeter. We required a lot of QA staff, but now we do not.

My experience with pricing, setup cost, and licensing has been that it is free only. Gatling Enterprise is open source, and licensing requires a third-party license, but it is easy.

Before choosing Gatling Enterprise, we evaluated JMeter versus Gatling Enterprise and found Gatling Enterprise to be much better.

If you are a small developer team, then it is good to have Gatling Enterprise for testing purposes. I found this interview good and do not believe anything needs to change for the future. My overall review rating for Gatling Enterprise is 8.