Gatling Enterprise Cloud

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.

Amazon Web Services (AWS)

What do you like best about the product?

Ability to simulate realtime traffic by mocking up workflows, adjust load distributions across multiple protocols and support for high loads

What do you dislike about the product?

There were quite a few changes going from 3.3.1 to 3.15, which forced us to rewrite most of our simulations including a custom plugin

What problems is the product solving and how is that benefiting you?

To simulate peak production traffic across multiple applications at the same time. We also run resiliency tests.

What do you like best about the product?

I like Gatling’s high performance, code-based scripting, and detailed performance metrics. I can simulate realistic user traffic and journeys, control concurrent users, ramp-up rates, and request arrival rates, and use assertions and response-time percentiles to validate performance thresholds. I can analyze response times, throughput, and error rates efficiently, and identify and resolve bottlenecks before they affect end users. Gatling was easy to set up.

What do you dislike about the product?

I think Gatling could be more user-friendly. A more intuitive visual interface for creating test scenarios, configuring virtual users, and setting load profiles would help beginners get started without extensive coding knowledge. I’d also like clearer error messages and better debugging support for complex scripts, along with an improved performance analysis workflow.

What problems is the product solving and how is that benefiting you?

Gatling helps me identify and resolve performance issues before they impact end users. I can simulate real-world traffic, measure application performance, and identify bottlenecks under different load conditions.

What do you like best about the product?

Flexibly coding tools, nice reporting and clear syntax

What do you dislike about the product?

It might be hard to set up a project architecture

What problems is the product solving and how is that benefiting you?

Helps to build userflow and analyze bottlenecks in app architecture

What do you like best about the product?

Gatling generates remarkably clean, detailed, and actionable out-of-the-box HTML reports. The real-time metrics and breakdown of response times, percentiles, and request distributions make it very easy to pinpoint bottlenecks quickly without needing complex external monitoring setups.

What do you dislike about the product?

The initial setup and scripting can be slightly time-consuming for engineers unfamiliar with Scala/Java DSLs, and running distributed tests natively requires setting up Gatling Enterprise or extra infrastructure scripting.

What problems is the product solving and how is that benefiting you?

Problems solved: Identifying specific performance bottlenecks, latency spikes, or response time degradations often requires setting up third-party dashboard tools just to read test output clearly.
​How it benefits me: Gatling generates detailed, out-of-the-box HTML reports with clear percentiles, response distributions, and error breakdowns. It speeds up my root-cause analysis, allowing me to quickly provide clear, actionable insights to development teams on where optimization is needed.

What do you like best about the product?

I like that Gatling helps me test the communication between services conveniently, letting me run tests after updating code without any problems. I also appreciate Gatling's structure, which organizes my base simulation and allows me to develop specific tests from that base class. The initial setup was fairly easy because I had some training, and the documentation made it understandable to implement the simulations. Overall, it's straightforward, and I can run the tests smoothly.

What do you dislike about the product?

For me the error displayed in the terminal is quite hard to read

What problems is the product solving and how is that benefiting you?

I use Gatling for end-to-end testing and testing communication between services, which it handles smoothly after code updates without issues.

What do you like best about the product?

I like that Gatling allows me to simulate realistic user loads with clear performance metrics, which helps me understand how APIs and workflows perform under stress. I appreciate that creating performance scenarios is easy and repeatable, making it useful for regression testing. The detailed reports on response time, throughput, and failures are incredibly helpful for identifying bottlenecks and communicating issues to the development team.

What do you dislike about the product?

One area where Gatling could be improved is the learning curve, especially for teams that are new to performance testing. Creating and maintaining complex scenarios can require a good understanding of the scripting approach and performance-testing concepts. The reporting and analysis are useful, but having more built-in visualization and easier-to-understand dashboards would make it simpler to interpret results for non-technical stakeholders. It would also be helpful to have more ready-to-use integrations and templates for common API and application performance-testing scenarios.

What problems is the product solving and how is that benefiting you?

Gatling helps me simulate user loads for API and application testing, identifying bottlenecks early. It offers visibility into response times, throughput, and system stability, making performance testing repeatable and ensuring our platform handles expected traffic.

What do you like best about the product?

I like Gatling's ease of use for load testing, especially compared to tools like JMeter. It's easier to write scripts and set up, and I appreciate that it's code-driven rather than UI-based. This makes reviewing code and writing custom scripts simpler. I also enjoy the integration with Jenkins, Grafana, and InfluxDB, which makes running and monitoring tests convenient. The support for Java and Scala is beneficial, and being able to handle a high load on instances is a big plus. The setup is quick and straightforward, which makes it a recommended choice for load testing.

What do you dislike about the product?

I think Gatling could be improved by providing more guidance on distributed load testing. It would be helpful if there were more resources like medium articles or guidelines, especially for organizations that can't afford the enterprise version. Having some directions or resources bundled in the free version would really benefit those users who need to perform distributed load testing without access to more expensive options.

What problems is the product solving and how is that benefiting you?

Gatling simplifies load testing by making it easy to write and review scripts without relying on UI-based tools. It's a scalable tool with powerful integrations like Jenkins, InfluxDB, and Grafana, allowing efficient load test automation and anomaly detection. It supports a code-driven approach, enhancing developer ease.

What do you like best about the product?

What I like most about Gatling is its powerful combination of developer-centric + qa-centric, code-based test scenarios in Scala and its high-performance asynchronous Netty architecture. Writing test scripts as code allows them to live right alongside the application repository and version control, while the non-blocking Netty engine effortlessly generates massive load with minimal resource overhead, making it exceptionally reliable and precise for performance evaluations on large scale systems, especially on Microservices layouts.

What do you dislike about the product?

For members without prior "JVM" or functional programming experience the primary learning curve involved in writing test scenarios through its Domain-Specific Language can be "steep". Additionally, running distributed load tests across multiple injectors or tracking real-time telemetry during active execution requires extra configuration outside of its out-of-the-box local reporting setup if you compare it with other tools like K6, although I personally believe that Gatling can be better tailored than the aforementioned.

What problems is the product solving and how is that benefiting you?

Gatling eliminates the heavy resource consumption and maintenance overhead of legacy thread-based tools by utilizing a non-blocking architecture, which benefits our workflow through:

- Closer Collaboration as Developers and QA engineers share the same environment, embedding performance checks into the pipeline.

- Actionable Reporting with its "Out-of-the-box" metrics make it easy to quickly pinpoint and resolve bottlenecks.

What do you like best about the product?

It’s easy to record network traffic, which makes it great for back-end performance testing. It can also be integrated with real-time data display tools like Grafana. Easy for implementing in a remote server and for daily load testing. Written in Java code, it allows users to implement highly complex user scenarios. Having the free tier version to begin. Newly AI integration. Supporters are highly available.

What do you dislike about the product?

Having fewer useful features in the free tier version than the enterprise version.

What problems is the product solving and how is that benefiting you?

Gatling allows our company to define the load capacity and security capacity of our services with less cost and easy maintenance.