Your Gatling tests are code. OctoPerf is everything around them.

Distributed load from the cloud or your own network, every report kept and compared, servers monitored, and a team working on the same tests.

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Gatling, Java

http("Search #{term}")
  .post("/actions/Catalog.action")
  .formParam("keyword", "#{term}")
  .check(regex("productId=([^\"&]*)")
    .findRandom().saveAs("productId"))

K6 Virtual User, on OctoPerf

const search = request('POST', 'Search',
  '/actions/Catalog.action',
  { keyword: term, searchProducts: 'Search' });
const productIds = findAll(search,
  /productId=([^"&]*)/g);

Features	OctoPerf vs. Gatling Open Source
Scripting	Codeless JMeter, or code with K6 and Playwright	Code only
Distributed Load	Cloud and on-premise load generators	One machine per run
Reports	Kept, compared and trended	One static HTML report per run
Real Browsers	Playwright Virtual Users and Core Web Vitals	Protocol level only
Server Monitoring	Built in, with alarms	Not included
Migration Off the Tool	AI-assisted: survey, then rewrite as K6	Rewrite by hand
	See the Pricing

The Platform Gatling Teams Grow Into

OctoPerf offers all testers a user-friendly continuous testing platform by combining advanced features with an unparalleled value-based pricing model.

A Gatling simulation is a good test. What it leaves to you is the rest: spreading the load over several machines, keeping every report, comparing a run with the last one, watching the servers while it runs. OctoPerf runs JMeter, K6 and Playwright in the same scenarios and the same reports, in the cloud or on premise.

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New in OctoPerf 18

Migrate Your Gatling Simulations With an AI Agent

OctoPerf does not run Gatling: it runs K6, and the two DSLs are close. OctoPerf ships a Gatling migration playbook for AI agents, and its first job is not a rewrite - it is a survey.

Survey first, read-only. Java, Scala or Kotlin: a portability verdict, an inventory of requests, checks, feeders and loops, and every construct with no K6 counterpart, by source and line.
Rebuild the load first. Closed injections carry over stage for stage. Open ones are rebuilt as paced users from a measured journey, and the numbers are written down.
Rewrite, then work one list. Requests, checks, extractors and feeders convert mechanically. Session code, retries and assertions come back as entries to finish.
Validate before scaling. Replay the K6 Virtual User on a real load generator, read its log and its exchanges, before you spend a test hour at scale.

Read the Walkthrough See How It Works

"Here is a Gatling project. Before converting anything, tell me whether it is worth migrating."

"portability": "ASSISTED",
"languages": ["JAVA"],
"inventory": {
  "httpRequests": 11, "checks": 5,
  "extractors": 3, "feeders": 2,
  "pauses": 10, "loops": 2,
  "sessionFunctions": 2
}

Three verdicts: MECHANICAL validates nearly as it is, ASSISTED converts then works the list, MOSTLY_MANUAL means a protocol or a library no K6 rewrite reaches. The survey writes nothing and costs nothing.