Sold by: Gatling Corp
Gatling Enterprise is Gatling's Business Version. Gatling Enterprise helps you manage all aspects of load testing through its web interface. Run your Gatling's simulations and get access to advanced features!
4.4
Overview
Gatling Enterprise is the official cloud solution of the open-source solution, Gatling. Gatling is one of the leading load testing solutions, designed for DevOps and CI/CD.
Anticipate crashes and performance issues, investigate your application's bottlenecks and become the leader of your industry.
Gatling promotes a "Load Test As Code" approach, designed for integration and automation. Gatling integrates a lightweight scripting DSL, a web recorder, the support of various protocols, a Jenkins' plugin to automate your tests and many more features.
Gatling Enterprise Cloud helps you manage your load testing strategy at the scale of your entire organization. Run your Gatling's simulations and get access to advanced features: New metrics (TCP connections, bandwidth usage, DNS resolutions, injectors' monitoring, trends) on live reporting; Clustering (for large-scale load testing campaigns); Tests history; Collaboration features (teams, rights and permissions); More integrations available (Github actions, Gitlab CI and more to come).
Take Gatling to the next level with Gatling Enterprise.
Useful links:
- Our official website page about Gatling Enterprise: https://gatling.io/enterprise/
- For support question, please contact us: https://gatlingcorp.atlassian.net/servicedesk/customer/portal/8
Highlights
- Live reporting, various metrics (requests' response times, TCP connections, bandwidth usage, DNS resolutions, injectors' monitoring) and trends
- CI plugins (Jenkins, TeamCity, Bamboo), public APIs, Grafana datasource
- And much more! More info: https://gatling.io/enterprise/
Details
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Delivery method
Deployed on AWS
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Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/month |
|---|---|---|
Scout 500 | 500 minutes | $99.00 |
Scout 1000 | 1000 minutes | $198.00 |
Scout 1500 | 1500 minutes | $297.00 |
Scale 2000 | 2,000 minutes | $396.00 |
Scale 4000 | 4,000 minutes | $792.00 |
Scale 6000 | 6,000 minutes | $1,188.00 |
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no refunds
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Support
Vendor support
Support portal where you can create a ticket in case of a technical issue or if you need assistance
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Updated weekly
By Gatling Corp
By Artillery
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In Testing
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In Application Performance and UX Monitoring
Sentiment is AI generated from actual customer reviews on AWS and G2
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AI generated from product descriptions
Load Testing Protocol Support
Supports various protocols for comprehensive load testing scenarios and application performance validation
Live Reporting and Metrics
Provides live reporting with metrics including request response times, TCP connections, bandwidth usage, DNS resolutions, and injectors' monitoring with trend analysis
Distributed Load Testing
Enables clustering capability for large-scale load testing campaigns across multiple injectors
CI/CD Integration
Integrates with CI/CD platforms including Jenkins, TeamCity, and Bamboo plugins, along with public APIs and Grafana datasource support
Test Management and Collaboration
Offers test history tracking, team-based collaboration features with configurable rights and permissions management
Multi-Framework Support
Supports JMeter, Gatling, Locust, Node.js (HTTP, websockets, Socket.io, Engine.io), Webdriver.io, Selenium Java, Serenity BDD, PhantomJS, SlimerJS, record-and-replay, and HAR files for test definition
Distributed Load Generation
Coordinates distribution of tests and real-time aggregation of results across multiple EC2 instances with unlimited virtual users per instance
Performance Analytics and Reporting
Provides percentiles, success analytics, trend analysis, and customizable result views for all metrics with capability to track concurrent user capacity across test runs
Automatic Scaling and Alerting
Automatically scales to detect and alert on the number of concurrent users that meet defined performance requirements and custom success criteria
Integration with Monitoring and CI Tools
Integrates with leading monitoring tools like NewRelic and CI solutions to embed load testing and monitoring into software development lifecycle
Centralized Test Reporting
Central dashboard aggregating Playwright test results with inline traces, screenshots, and CI integrations for unified visibility across test executions.
Multi-Protocol API Testing
Support for multiple protocols including HTTP, GraphQL, WebSocket, and Socket.IO for comprehensive API-level testing capabilities.
Distributed Load Testing
Load testing execution from multiple geographic regions using organization's own AWS accounts with support for complex web applications.
Test Observability and Tracing
Real-time monitoring with custom charting, visualization capabilities, and tracing support for Playwright and HTTP tests to identify and debug performance issues.
Synthetic Monitoring
Synthetic monitoring capabilities using Playwright for continuous application performance validation and availability verification.
Standard contract
No
No
Customer reviews
Andrii O.
Gatling’s Code-First Performance Testing Fits Perfectly into Our Workflow
Reviewed on Jul 29, 2026
Review provided by G2
What do you like best about the product?
I like best about Gatling is its code-first approach to performance testing. Test scenarios are written as maintainable code, which makes them easier to review, version, refactor, and integrate into a regular development workflow.
What do you dislike about the product?
the initial learning curve. The DSL is elegant once you understand it, but engineers without experience in Scala or functional programming concepts may find the syntax and error messages less approachable than JMeter’s graphical interface. Also we need more steps to set everything up to work with Scala. However, it is possible to choose Kotlin or Java instead.
What problems is the product solving and how is that benefiting you?
Gatling solves the problem of creating maintainable and repeatable performance tests for APIs and web applications. It allows performance scenarios, workload models, test data, checks, and assertions to be defined as code and stored together with the application or test project.
Compared with GUI-based tools such as JMeter, Gatling makes collaboration through Git more practical. Changes are easier to review, merge, and track, especially when the performance test suite becomes larger and more complex.
It is possible to execute Gatling from Ci CD pipelines and collect the results automatically
Compared with GUI-based tools such as JMeter, Gatling makes collaboration through Git more practical. Changes are easier to review, merge, and track, especially when the performance test suite becomes larger and more complex.
It is possible to execute Gatling from Ci CD pipelines and collect the results automatically
shivangi j.
Great tool to Boost Legacy App Performance
Reviewed on Jul 29, 2026
Review provided by G2
What do you like best about the product?
Its really good tool for load testing tool i actually use it for my old legacy app and it really helped me to improve the app performance.
What do you dislike about the product?
It’s difficult for an end user to understand the UI, so it could be improved in that area to make it clearer and easier to use.
What problems is the product solving and how is that benefiting you?
We were struggling with performance issues in our app. Since the app was live and a legacy application, we were dealing with production issues on a daily basis. To address all of that, we decided to go with Gatling.
Anonymous
Developer-Friendly with a Learning Curve
Reviewed on Jul 28, 2026
Review provided by G2
What do you like best about the product?
I like that Gatling is a non-GUI, developer-centric tool. The fact that scripts can even be AI-generated is pretty cool, and I find the memory footprint per script to be actually minuscule. It's efficient enough that I can use a single VM to run over 500 threads. I also appreciate how Gatling can be integrated into our dev workflows, allowing Claude to auto-generate Gatling scripts as we develop and build APIs. Additionally, AI can go through Postman collections to create a complete Gatling suite of scripts. Setting up Gatling was rather easy, with no problems there.
What do you dislike about the product?
Since Gatling is non-GUI, I find it has a learning curve for us non-developers. It takes time for us to figure out the functions and features. Also, I face challenges because Gatling requires Scala, and I had to cross-train Java developers to read and understand Scala code.
What problems is the product solving and how is that benefiting you?
I use Gatling for scripting end-to-end business workflows, creating reusable templates, and scaling our performance testing frameworks. The low memory footprint allows running 500+ threads on a single VM. It integrates with our dev workflows for auto-generating scripts.
Muhammed Sameer S.
Gatling Makes Performance Testing Efficient with Flexible, CI/CD-Friendly Workflows
Reviewed on Jul 27, 2026
Review provided by G2
What do you like best about the product?
What I like most about Gatling is how easy it is to create and maintain performance tests. As an automation tester, I find its code-based approach more flexible than record-and-playback tools. It integrates smoothly with CI/CD pipelines, generates clear and detailed reports, and helps identify performance issues quickly. Overall, it's a reliable tool that makes performance testing efficient and fits well into modern automation workflows.
What do you dislike about the product?
One thing I dislike about Gatling is that it has a bit of a learning curve, especially if you're new to Scala or its scripting syntax. Creating complex test scenarios can take more effort compared to some GUI-based tools. Also, debugging scripts isn't always straightforward, and some advanced features require extra setup. That said, once you're familiar with it, the flexibility and performance make it worth using.
What problems is the product solving and how is that benefiting you?
Gatling helps us identify performance bottlenecks before applications go live by simulating real user traffic and measuring how the system behaves under load. As an automation tester, it gives me confidence that new features can handle expected traffic without affecting performance. It also helps catch issues early in the development cycle, supports continuous testing through CI/CD integration, and provides detailed reports that make it easier to analyze results and share insights with the team.
Marek S.
A flexible tool for building complex performance tests
Reviewed on Jul 23, 2026
Review provided by G2
What do you like best about the product?
What I like most about Gatling is its flexibility and the ability to build complex performance test scenarios as code. It gives me full control over test flows, dynamic data, request generation, and different load injection models.
I particularly appreciate that Gatling can be extended beyond standard HTTP testing. In my case, I use it for complex SOAP-based scenarios with dynamic request generation, WS-Security signing, custom mock services, and multi-step transaction flows. The Java-based DSL also makes it easier to structure, maintain, and reuse test components compared to traditional GUI-based performance testing tools.
Another strong point is the clear separation between test logic, request generation, and load profiles, which makes the test project easier to develop and integrate into CI/CD pipelines.
I particularly appreciate that Gatling can be extended beyond standard HTTP testing. In my case, I use it for complex SOAP-based scenarios with dynamic request generation, WS-Security signing, custom mock services, and multi-step transaction flows. The Java-based DSL also makes it easier to structure, maintain, and reuse test components compared to traditional GUI-based performance testing tools.
Another strong point is the clear separation between test logic, request generation, and load profiles, which makes the test project easier to develop and integrate into CI/CD pipelines.
What do you dislike about the product?
There is not much I dislike about Gatling itself. One challenge is that more complex or non-standard use cases can require additional custom development and a deeper understanding of the underlying technologies. For example, working with SOAP, WS-Security, or custom mock services requires building some functionality yourself.
However, this is also a consequence of Gatling's flexibility, as it gives you the freedom to implement scenarios that go beyond typical HTTP/REST performance testing.
However, this is also a consequence of Gatling's flexibility, as it gives you the freedom to implement scenarios that go beyond typical HTTP/REST performance testing.
What problems is the product solving and how is that benefiting you?
Gatling helps us validate the performance and stability of our systems under different load conditions before changes reach production. It allows us to simulate realistic, multi-step transaction flows and control how the load is generated, from gradual ramp-up to sustained concurrency and peak-load scenarios.
The main benefit is repeatability and automation. Performance tests can be maintained as code, reused across different scenarios, and integrated into CI/CD processes. This makes it easier to identify performance bottlenecks, compare system behavior between releases, and reproduce specific load conditions when investigating performance issues.
The main benefit is repeatability and automation. Performance tests can be maintained as code, reused across different scenarios, and integrated into CI/CD processes. This makes it easier to identify performance bottlenecks, compare system behavior between releases, and reproduce specific load conditions when investigating performance issues.