# Gatling Enterprise review

> Gatling Enterprise is the right paid step for teams that already like Gatling's code based simulations but need distributed load, team controls, and live reporting without inventing their own platform. The current plans start at EUR 89 per month when billed annually, which is more transparent than many enterprise tools, but the cost grows with load generators and test minutes. Choose it for serious Gatling programs; use open source Gatling for local, single injector work.

- Canonical: https://perf.jmeter.ai/reviews/gatling-enterprise/
- Tool page: https://perf.jmeter.ai/tools/gatling-enterprise/
- Reviewed: 2026-09-17 · Desk review

## Verdict
Gatling Enterprise is the right paid step for teams that already like Gatling's code based simulations but need distributed load, team controls, and live reporting without inventing their own platform. The current plans start at EUR 89 per month when billed annually, which is more transparent than many enterprise tools, but the cost grows with load generators and test minutes. Choose it for serious Gatling programs; use open source Gatling for local, single injector work.

### Pick it when
- Gatling simulations already live in the delivery workflow
- Distributed public, private cloud, or on premises injection is required
- Teams need central permissions and live results

### Skip it when
- One local injector and the open source report are enough
- The test authors need a visual, recorder led workflow
- Usage credits cannot be estimated or governed

## What Gatling Enterprise is
Gatling Enterprise is the commercial platform around the Gatling engine. Simulations remain source code, written in Java, JavaScript, Kotlin, Scala, or TypeScript, while the platform manages packages, users, load generators, execution, and results. It can run from managed public locations, inside a customer cloud account, or on premises. That separation is sensible: engineers keep tests in Git and operators get one place to control capacity and access.
The protocol catalog now includes HTTP, WebSocket, SSE, JMS, MQTT, and gRPC. HTTP is still the mature path. Do not mistake protocol support for a browser renderer: an HTTP simulation models requests, cookies, caching, and redirects, but it does not execute page JavaScript like a real browser.

## What you get
The useful additions over community Gatling are distributed load generation, live dashboards, scheduled runs, permissions, and central retention of results. A public API can launch a run or fetch metrics with an API token, which is enough to make a pipeline wait on a test and apply a clear threshold. Private locations are especially valuable when an API is behind a firewall or when data must stay in a chosen network.
Pricing is published. The Basic plan is EUR 89 per month billed annually and includes a limited starter allocation, while Team adds more generators and capacity. That is easier to budget than a pure quote model, but test minutes are credits, so a long high scale run consumes more than a short smoke check. Estimate the load model before committing a recurring gate.

## Where it falls short
Enterprise does not make Gatling a no code tool. The DSL is a benefit for engineers, but a test analyst who needs a visual recorder first may reach productivity sooner in JMeter, NeoLoad, or LoadRunner. Community Gatling already has a strong local report, so a team should buy Enterprise for coordination and distributed capacity, not just to get a prettier chart.
The usage model deserves attention. Generator count, run duration, seats, data retention, and private location needs all affect the final cost. I would run a representative test in the trial and check the reported credits before copying a daily performance gate across every service.

## AI features
Gatling now lists AI coding assistants, JMeter conversion, an MCP server, and AI insights on reports in its commercial offering. Those can reduce the first draft and help an engineer navigate a report. They do not know your business transactions or acceptable degradation, so I would still write the checks, injection profile, and success criteria by hand.

## Bottom line
Bottom line: Gatling Enterprise is a strong fit when code based Gatling tests need reliable distributed execution, access controls, and a shared result history. Pick open source Gatling for local work, or choose a GUI led suite when your authors are not comfortable owning simulations as code.

## About this review
Desk review: based on current docs, release notes and prior experience. I did not run the current release for this review.

## Ratings
| Dimension | Level | Note |
| --- | --- | --- |
| Scripting & extensibility | Strong | Typed SDKs support Java, JavaScript, Kotlin, Scala, and TypeScript. |
| Protocol coverage | Strong | HTTP, WebSocket, SSE, JMS, MQTT, and gRPC cover modern service tests. |
| Scale & distribution | Strong | Managed and private generators support distributed execution. |
| Reporting & analysis | Strong | Live dashboards and retained results add to Gatling's local report. |
| CI/CD & automation | Strong | The public API and CI scripts make runs automatable. |
| Cost & licensing | Adequate | Published entry pricing helps, but capacity is consumed as test credits. |
| AI features | Adequate | Assistants, converters, MCP, and report insights are listed commercially. |

## Pros
- Keeps Gatling simulations in source control
- Adds managed and private distributed load generation
- Live dashboards, permissions, and shared result history
- Published starting price and a trial path

## Cons
- Still expects authors to work comfortably in code
- Usage credits make recurring high scale testing a budgeting task
- Browser level behavior needs a different tool
- Community edition already covers many local use cases

## FAQ
### Is Gatling Enterprise worth it in 2026?
Gatling Enterprise is the right paid step for teams that already like Gatling's code based simulations but need distributed load, team controls, and live reporting without inventing their own platform. The current plans start at EUR 89 per month when billed annually, which is more transparent than many enterprise tools, but the cost grows with load generators and test minutes. Gatling simulations already live in the delivery workflow

### When should you pick Gatling Enterprise?
Gatling simulations already live in the delivery workflow Distributed public, private cloud, or on premises injection is required Teams need central permissions and live results Together, these are the clearest signals that Gatling Enterprise fits the project. Compare the current documentation, operating model, and total cost with the project requirements before making a final decision.

### When should you skip Gatling Enterprise?
One local injector and the open source report are enough The test authors need a visual, recorder led workflow Usage credits cannot be estimated or governed Treat these constraints as reasons to compare alternatives before committing to Gatling Enterprise. Compare the current documentation, operating model, and total cost with the project requirements before making a final decision.

### Does Gatling Enterprise have AI features?
Assistants, converters, MCP, and report insights are listed commercially. Check the current product documentation before relying on these capabilities in production. Compare the current documentation, operating model, and total cost with the project requirements before making a final decision.

---
Curated by NaveenKumar Namachivayam (QAInsights) · methodology: https://perf.jmeter.ai/about/#methodology · corrections: https://github.com/QAInsights/Performance-Testing-Tools/issues/new?title=Tool%20submission%3A%20&body=Tool%20name%3A%20%0AOfficial%20URL%3A%20%0AWhat%20should%20be%20added%20or%20corrected%3F%20%0A