Gatling

docs.gatling.io ↗

Write load-test scenarios as code and control the request rate sent to an application.

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Screenshot of the Gatling homepage

What it does

Gatling is a performance-testing platform whose test-as-code workflow defines virtual users, requests, and load profiles in a simulation. The JavaScript guide builds a test incrementally, configures an HTTP target and scenario, then chooses an injection profile. Results help teams examine how an application behaves under the specified traffic pattern.

The JavaScript tutorial starts from a prepared project and adds a simulation, HTTP protocol, scenario, and injection profile in separate steps. One example configures a constant rate of two users per second for one minute. That is an illustrative tutorial workload, not a recommendation for a production system: set the base URL and request behavior for a system you are authorized to test, then increase load gradually while watching response data and target-system health.

Gatling can run a simulation locally and also describes packaging it for Enterprise. Its pricing page separates the Community edition from commercial collaboration and hosted load-testing capabilities. That choice matters because a local tool consumes the runner’s own resources, while a managed load-testing service changes where traffic originates and what coordination is needed. A successful simulation launch is not proof that the target can handle a different traffic profile.

Strengths

  • The JavaScript tutorial constructs a simulation from protocol, scenario, and injection-profile pieces.
  • The guide includes a local run workflow and a path to Gatling Enterprise.
  • The pricing page distinguishes Community and Enterprise editions.

Watch out for

  • A load test generates traffic against a target, so the operator must supply a valid target and an appropriate workload profile.
  • Local execution is bounded by the runner’s resources; hosted execution has different plan and coordination requirements.

Best for

  • Writing repeatable HTTP load simulations as code
  • Comparing application behavior under a controlled request-rate profile

Sources