Why should you use Gatling for Load testing

Gatling uses an innovative asynchronous architecture to simulate thousands of concurrent users efficiently and is widely adopted by organizations aiming to load-test their applications.

Learn why you should use Gatling for Load Testing, how it differs from Apache Jmeter and more in this detailed tutorial.

What is Gatling

Gatling is an open-source load testing tool designed for testing the performance of web applications. It is written in Scala and uses a domain-specific language (DSL) for scripting. Gatling is ideal for developers who prefer code-based test creation. It is known for its asynchronous, non-blocking architecture, which allows it to simulate a large number of virtual users with fewer system resources.

Gatling’s powerful engine and detailed HTML reports make it a strong choice for continuous integration (CI/CD) pipelines and performance testing in modern DevOps workflows.

Gatling Versions

Here are the various versions of Gatling and their key functionalities:

Gatling 3.x is the most widely used and actively maintained version, offering the best combination of speed, scalability, and integration. Enterprise version (Gatling FrontLine) is ideal for organizations needing security, reporting at scale, and collaboration in CI/CD pipelines.

Features of Gatling

Given below are the key features of Gatling that enhance load testing:

• Rich Feature Set: Includes sophisticated request and response processing, data extraction, and conditional assertions, allowing the creation of realistic user behavior simulations.
• Comprehensive Metrics and Dashboards: Provides built-in dashboards for monitoring performance and analyzing results, enabling quick identification of performance bottlenecks.
• Performance Monitoring: Real-time monitoring can be integrated with tools like Grafana or Prometheus for immediate insights into performance metrics.
• Community and Support: Strong community support with active participation and best practices sharing. Robust customer support is available for complex use cases.
• Comprehensive Reporting and Resources: Detailed reports are generated, including response times, throughput, and error rates, to pinpoint performance bottlenecks. A Domain Specific Language (DSL), such as Meta DSL, simplifies the definition of global settings and configurations.
• Powerful Engine: Can generate millions of users seamlessly and supports on-premises load generators. It also provides managed infrastructure and Kubernetes support and supports major cloud providers like AWS, Google Cloud Platform, and Azure.
• Integrations: Offers CI/CD integrations, supports various APM tools and notifications, provides protocol support, and integrates with build tools like Maven, Gradle, and SBT.

Why Use Gatling for Load Testing

Here’s why you might choose Gatling for load testing:

1. Asynchronous Architecture for Scalability: Gatling’s asynchronous architecture allows it to simulate thousands of concurrent users on a single machine without excessive resource consumption. It uses messages for virtual users instead of dedicated threads.

2. Comprehensive Performance Monitoring: Gatling is all about monitoring critical performance indicators such as response time, error rate, average CPU/memory utilization, and throughput.

3. Detailed Reporting and Visualization: Gatling has built-in, interactive dashboards where you can cherry-pick the metrics you desire to analyze regarding performance. These reports give details on transaction response times, throughput, and occurrences of errors.

4. Ease of Use (“Load-Test-as-Code”): Supports a “load-test-as-code” methodology that is ideal for DevOps and CI/CD workflows. You can set them up and then run your tests from your local machine.

5. Components to Enhance Load Testing: Gatling consists of several key components that work together to facilitate load testing. Unlike LoadRunner, Gatling is code-first and DevOps-integrated:

• Scripting: Tests are written in code (Scala/Java/Kotlin/JS) or recorded via the no-code web recorder. Scripts are version-controlled and IDE-friendly.
• Execution: It runs via CLI or CI/CD (e.g., Jenkins).Gatling Enterprise provides a centralized interface to manage tests with auto-scaling load generators.
• Load Generation: Gatling’s architecture uses asynchronous, message-based virtual users, enabling high concurrency (up to 60k users per generator). It also enables distributed testing in cloud/on-premises (AWS, Kubernetes, etc.).
• Reporting: HTML reports with response times, metrics, and comparisons.

6. Versatility and Compatibility: Compatible with multiple platforms and environments and can be integrated into CI/CD pipelines. Gatling supports over 10 web protocols and offers test-as-code using JavaScript, TypeScript, Java, Kotlin, and Scala.

7. Enhanced Testing Capabilities: Supports various testing types like unit, integration, and automated acceptance testing. It allows dynamic data feeding through CSV or JSON for realistic data inputs.

How to Install Gatling

Gatling can be easily downloaded by visiting the official website. Users have two options for download: an Enterprise version, which includes additional features for a fee, and an open-source version that is available for free.

For demonstration purposes, it is recommended to select the open-source version. Once the download is complete, the user should unzip the folder, where all necessary files to run Gatling are located.

Configuration

After unzipping the Gatling folder, users should locate the gatling.conf file formatted in JSON, which contains configurable settings for Gatling, including default values. It is essential to modify this configuration file to set the directory paths for simulations and resources.

Specifically, users should navigate to the directory section and uncomment the relevant lines for simulations, resources, and results directories to ensure Gatling can locate the necessary files during execution.

Directory Settings

In the configuration file, the following settings should be adjusted:

• simulations: This setting points to the location where simulation classes are stored, typically under

../user-files/simulations

• resources: This specifies the directory for resources, such as feeder files and request bodies, generally set to

../user-files/resources

• results: This defines where the reports will be stored after a load test is completed, often set as results.

Final Steps

Once the configuration is adjusted, users are ready to execute their performance tests using Gatling. It is crucial to ensure that all required files and directories are correctly set up to facilitate a smooth testing experience.

How to Use Gatling  [Sample Script Execution]

Here’s how you can use Gatling:

1. Install Gatling: Download Gatling from the official website. Make sure you also have Java installed, as it’s required to run Gatling.

2. Set up the Project: Create a new directory for your project if you’re starting from scratch. Alternatively, you can use an existing Gatling project.

If creating a new project with Maven, use the following command:

mvn archetype:generate -DarchetypeArtifactId=maven-archetype-quickstart -DinteractiveMode=false

3. Create a Simulation Script:

• You can write your Gatling test scripts in Scala, Java, or Kotlin.
• A basic script includes sections for Protocol, Scenario, and SetUp.
• Use the Recorder to generate a basic script by recording your actions on a web browser. Gatling comes with an easy to use graphical test recorder which can generate simulation scripts by recording user activity or user actions on a web browser.
• Define the scenario that virtual users will execute using exec to attach a chain or execute a request or a function. Use loops such as repeat.

4. Configure the Simulation:

• Set up the simulation by defining things like the number of users, ramp-up time, and duration. For example:

setUp(

scn.inject(

rampUsers(20) during(10 seconds)

)

)

This code injects 20 users over 10 seconds.

5. Run the Simulation:

• Navigate to the Gatling directory in your terminal.
• Execute the simulation. If you are using Maven, you can use the command :

./mvnw gatling:test

6. Analyze the Report: After the simulation finishes, Gatling generates a detailed HTML report with performance metrics. Analyze the results to identify bottlenecks and areas for optimization.

What is Gatling Recorder and How it Works?

Before conducting tests, defining a scenario that accurately represents user interactions with the application is vital. These scenarios can be scripted in code or recorded using the Gatling Recorder, allowing flexibility and ease of maintenance.

Gatling Recorder is a tool within the Gatling load testing framework that simplifies the creation of performance testing scripts. It captures user interactions with a web application, acting as an HTTP proxy between the browser and server, or by converting HAR files.

Gatling’s powerful recorder that captures user interactions to create a Scala script representing the simulation. This script is designed to be self-explanatory, allowing for straightforward adjustments and updates. By utilizing a Domain-specific Language (DSL), developers can create and maintain complex test scenarios with relative ease, even though some familiarity with Scala may enhance the experience.

Gatling vs JMeter: Which is Better for Load Testing

One may choose Gatling if high-performance, code-driven load tests and working in a developer-oriented environment are important.

On the other hand, JMeter can be opted for if you need broader protocol support, easy GUI usage, and a rich plugin ecosystem with minimal coding.

Here’s a comprehensive comparison:

Why Use Real Devices with Gatling for Load Testing?

While Gatling excels at simulating traffic and measuring backend performance, it doesn’t reflect real user experience. Testing on real devices reveals how pages render, how UI elements respond, and how network conditions impact performance across different browsers and screen sizes.

BrowserStack makes this easy with access to 3500+ real Android and iOS devices. When integrated with Gatling or JMeter, it ensures your app is optimized not just for scalability, but for real-world user experience too.

Talk to an Expert

Conclusion

Gatling is a strong and versatile performance testing tool that meets the changing requirements of contemporary software development, emphasizing the importance of robust performance assessments in delivering high-quality digital experiences.

Although JMeter has wider protocol support, an intuitive GUI, and a vast plugin community, Gatling shines in scenarios demanding efficient, scalable, and code-driven load testing, making it a powerful choice for optimizing web application performance.

When combined with BrowserStack’s real device cloud, teams can go beyond backend metrics to assess real-world performance across 3500+ Android and iOS devices.

Try BrowserStack Now