Java load testing: Run performance tests with Gatling

Whether you're building a website, app, something based on microservice architecture, or a high-performance backend API, your Java application must scale under real-world load.

And that means you need proper load testing.

Traditional GUI tools or legacy scripting approaches don’t cut it for modern Java teams. You want:

• Full control in code
• Integration with your toolchain
• Reusable test logic
• Scalable test execution

Gatling delivers all that and more—with a developer-first experience, now fully Java-native.

Why load testing matters for Java applications

Skipping structured load testing often leads to surprises in production—things like:

• Memory leaks and long GC pauses
• Slow database queries under concurrent usage
• Thread pool exhaustion
• Application server lockups
• Outage-triggering race conditions

Done right, load testing helps you:

• Discover performance bottlenecks
• Validate scaling strategies
• Catch issues early in CI
• Prove readiness for peak traffic events

And for Java teams, that means finding a load testing tool that speaks your language—literally.

Gatling for Java: test as code, performance at scale

Gatling has always stood out for performance and developer experience. And with the Gatling Java SDK, Java developers get a first-class load testing experience—with clean syntax, CI-friendly execution, and an ultra-efficient core engine.

Writing load tests in Java with the Gatling SDK

Here's what makes the Gatling Java SDK powerful and intuitive for backend developers:

• Java-based syntax — no XML, no Groovy
• Use of lambdas, method chaining, and familiar Java types
• Static typing and IDE support (autocomplete, refactoring, linting)
• Easy integration into Maven or Gradle builds

Sample scenario

1. Set up your environment

Gatling recommends using the Java SDK with Maven unless you’re already experienced with Scala or Kotlin. You’ll need:

• Java 17 or 21 LTS. The sample project uses features introduced in Java 17, though the Gatling SDK supports Java 11 and later.
• A trial account on Gatling Enterprise (optional). Sign up to run tests in the cloud.
• The Gatling demo repository. Clone it from GitHub, open it in your IDE and navigate to the java/maven folder.

By establishing a consistent environment you’ll be ready to explore the survey questions around infrastructure (on‑prem servers, cloud VMs, managed Kubernetes, etc.) and see how Gatling fits into your stack.

1. Create a basic simulation

A Gatling simulation consists of four parts: imports, protocol configuration, scenario description and an injection profile. You’ll work in BasicSimulation.java:

1. Clean up the file: Delete everything below the import lines so that the class is empty.
2. Extend the Simulation class: create a public class that extends Simulation to make it a valid Gatling script.
3. Define the HTTP protocol: inside the class, build an HttpProtocolBuilder with a base URL and default headers. The tutorial’s example points to Gatling’s e‑commerce API, sets the acceptHeader to JSON and defines a user agent.
4. Describe the scenario: define a ScenarioBuilder that simulates a user journey. The basic example simply performs a GET request on /session. In a production test you might add requests to public or internal APIs, databases or SaaS endpoints, echoing the systems under test listed in our survey (APIs, on‑prem infrastructure, SaaS apps).
5. Set up the injection profile: specify how virtual users arrive. The introductory tutorial uses constantUsersPerSec(2).during(60) to inject two users per second for 60 seconds. This is where you translate your survey answers about how often you run tests (on every code change, daily, weekly, etc.) into concrete numbers.

When these elements are combined your simulation should resemble the following snippet from the documentation:

public class BasicSimulation extends Simulation {

 HttpProtocolBuilder httpProtocol =

   http.baseUrl("<https://api-ecomm.gatling.io>")

       .acceptHeader("application/json")

       .userAgentHeader("Mozilla/5.0 …");



 ScenarioBuilder scenario =

   scenario("Scenario").exec(http("Session").get("/session"));



 {

   setUp(scenario.injectOpen(constantUsersPerSec(2).during(60))).protocols(httpProtocol);

 }

}



1. Run the simulation

You can execute your simulation locally using Gatling’s Community Edition or remotely via Gatling Enterprise. For a quick manual run on the cloud:

1. Generate a package from the Maven project with ./mvnw gatling:enterprisePackage.
2. Upload the generated JAR file in the Gatling Enterprise console and create a new simulation.
3. Configure parameters such as simulation name, package and test location, then launch the test.

If you prefer local debugging, run ./mvnw gatling:test in the java/maven directory; select your simulation class and open the generated HTML report. The report will display key metrics like response time, percentiles and error rates—many of the same KPIs respondents flagged as important in our survey.

What’s next?

• Customize the injection profile: The constantUsersPerSec function is just one of many injection options. Explore ramping, closed‑model users and steps to match your workload patterns.
• Explore different protocols: Gatling supports WebSockets, MQTT, gRPC and more. This aligns with the varied protocols our survey respondents test.
• Integrate with CI/CD: Use Maven or Gradle plugins with Jenkins, GitHub Actions or other pipelines to automate your tests—an area many teams asked about in the survey.

For a longer version, find the full tutorial here.

Comparing load testing tools: Gatling vs JMeter vs k6 vs LoadRunner

Here’s how Gatling compares to other popular load testing tools used by Java teams:

When Gatling stands out

Gatling shines in scenarios where Java teams need:

• Fast, repeatable performance testing
• Scalable test execution from a single node
• Full control of user flows and data injection
• Easy maintenance of test code (version control, reviews)
• Automated test results with CI/CD pipelines

It’s especially useful when testing:

• REST APIs written in Java (Spring, Jakarta EE, Quarkus, etc.)
• Java-based microservices architectures
• Backend services with high concurrency or low latency needs

Scaling up: from local to enterprise-grade with Gatling

If your team is ready to go beyond local testing and manual reports, Gatling Enterprise Edition gives you the power and flexibility to run and manage tests at scale.

Here’s what you get when you level up:

Distributed load generation

Easily simulate high traffic from multiple geographic regions using coordinated load generators. You can run tests across different cloud providers or internal infrastructure without manual orchestration. Gatling Enterprise manages the distribution and aggregation for you.

Live monitoring during test execution

Track response times, error rates, and throughput in real time—while your test is running. Spot performance regressions, infrastructure failures, or slow endpoints instantly. You can pause or abort long-running tests if they’re clearly going south.

Result comparison and trend analysis

Visualize performance improvements (or regressions) across test runs. Gatling Enterprise stores results historically, so you can see how your application evolves over time—perfect for performance regression testing and reporting to stakeholders.

Collaboration and access control

Share simulations, reports, and dashboards with your team. Use role-based access control to define who can run, edit, or view results. This is especially useful for large engineering orgs or cross-functional testing teams.

No-code test creation from HAR and Postman

Gatling Enterprise lets non-developers convert recorded user journeys (HAR files) or API collections (from Postman) into Gatling simulations—lowering the barrier to entry for performance testing across QA and product teams.

CI/CD and toolchain integration

Trigger tests automatically in your CI pipeline using Jenkins, GitLab, or GitHub Actions. Send notifications to Slack or Microsoft Teams. Use the REST API to run simulations programmatically. Your performance tests become a seamless part of your DevOps workflow.

Learn more about Gatling Enterprise Edition

Gatling: modern load testing for Java, built by developers

Old tools expect you to adapt your process to their UI. Gatling lets you define your performance testing strategy in code, just like the rest of your software delivery pipeline.

• Java SDK
• Clean syntax
• Strong performance
• Seamless integration
• Proven scalability

For modern Java teams, Gatling isn’t just another load testing tool; it’s the one that fits.

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