Gatling Maven Project Setup Demo | Command Line Runs

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How to setup maven project (java & scala)
How to run maven commands
How to run specific test simulation
How to run multiple test simulation
Gatling Maven Project Setup
Step 1 - Check Prerequisites
java -version
mvn -version
Step 2 - On IntelliJ IDE Go to File ＞ New ＞ Project from Version Control
Paste the repository URL
Java - github.com/gat...
Scala - github.com/gat...
Step 3 - Select local folder, Click Clone
To view all dependencies goto File ＞ View ＞ Tool Windows ＞ Maven
For Scala project:
scala -version (not needed if scala plugin added on IntelliJ IDE)
check scala plugin is added in the IDE (File - Settings - Plugins)
can add scala in Project Libraries (File - Project Structure - Global Libraries - Scala)
In case the scala and resources folder not already marked
Rt click on scala folder ＞ Mark Directory as ＞ Test Sources root
Rt click on resources folder ＞ Mark Directory as ＞ Test Resources root
Step 4 - Open command line and goto the location of project folder
Try these commands:
mvn clean gatling:help
mvn clean gatling:verify
mvn clean gatling:recorder
mvn clean gatling:test
mvn clean gatling:test -Dgatling.simulationClass=com….Sim1
Can try running the Engine and Recorder classes manually and check
To run Multiple Simulations mvn clean gatling:test
Add in pom.xml
＜configuration＞
＜runMultipleSimulations＞true＜/runMultipleSimulations＞
＜/configuration＞
Ref:
gatling.io/202...
gatling.io/doc...
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Raghav Pal
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How to run Gatling from command line
How to run multiple simulations in Gatling from commandline
Gatling maven project with commands

[@pratikchauhan4566]

Hi, thank you for sharing informative video on Gatling.
I have started exploring Gatling where i am trying to do research on externalizing configuration like API base uri, headers, request payload ...etc for simulation class...
Can you share your thoughts on how to do it ??

[@RaghavPal]

Pratik
Gatling provides several ways to externalize configuration. Here are a few options:
* Properties files: You can store configuration values in a properties file (e.g., `application.properties`) and load them in your simulation.
* Environment variables: You can set environment variables and access them in your simulation using the `System.getProperty()` method.
* Configuration classes: You can create a configuration class that holds the values and inject it into your simulation.
For this example, let's use the properties file approach.
Step 1: Choose a configuration approach
Gatling provides several ways to externalize configuration. Here are a few options:
* Properties files: You can store configuration values in a properties file (e.g., `application.properties`) and load them in your simulation.
* Environment variables: You can set environment variables and access them in your simulation using the `System.getProperty()` method.
* Configuration classes: You can create a configuration class that holds the values and inject it into your simulation.
For this example, let's use the properties file approach.
Step 2: Create a properties file
Create a file named `application.properties` in the root of your project (or in a location that's accessible by your simulation). Add the configuration values you want to externalize, such as:
```properties
api.base.uri=example.com/api
api.headers.Content-Type=application/json
api.request.payload={"key": "value"}
```
Step 3: Load the properties file in your simulation
In your simulation class, add the following code to load the properties file:
```scala
import io.gatling.core.Predef._
import io.gatling.http.Predef._
class MySimulation extends Simulation {
val props = new Properties()
props.load(new FileInputStream("application.properties"))
val apiBaseUri = props.getProperty("api.base.uri")
val apiHeaders = Map("Content-Type" -> props.getProperty("api.headers.Content-Type"))
val apiRequestPayload = props.getProperty("api.request.payload")
// Use the externalized configuration values in your scenario
val scn = scenario("My Scenario")
.exec(http("Get API")
.get(apiBaseUri + "/ endpoint")
.headers(apiHeaders)
.body(StringBody(apiRequestPayload))
)
}
```
In this example, we load the `application.properties` file using the `Properties` class and retrieve the values using the `getProperty()` method. We then use these values to configure our HTTP request.
Step 5: Run your simulation
Run
-

[@pratikchauhan4566]

@@RaghavPal
Thank you so much for the detailed explaination .. this really helped me !!

[@sonalahluwalia]

Hi Raghav.
I have another query...please help me out.
How to do LLM testing.

[@RaghavPal]

Sonal
LLM testing stands for Load, Latency, and Memory testing. Let's break down each component:
1. Load Testing:
- Purpose: Load testing evaluates how well a system performs under expected and peak loads.
- Process:
- Identify critical scenarios (e.g., user registration, checkout process).
- Create test scripts that simulate user interactions (using tools like JMeter, Gatling, or custom scripts).
- Gradually increase the load (number of concurrent users or requests) to observe system behavior.
- Monitor response times, resource utilization, and errors.
- Analyze bottlenecks and optimize system components.
2. Latency Testing:
- Purpose: Latency testing assesses the delay between sending a request and receiving a response.
- Process:
- Measure the time taken for various operations (e.g., database queries, API calls, page rendering).
- Use tools like Ping, Traceroute, or specialized latency measurement tools.
- Set acceptable latency thresholds based on user expectations.
- Investigate high latency areas and optimize them.
3. Memory Testing:
- Purpose: Memory testing ensures that an application manages memory efficiently.
- Process:
- Monitor memory usage during different scenarios (e.g., login, data processing).
- Use tools like Valgrind, JConsole, or built-in profilers.
- Check for memory leaks (unreleased memory) and excessive memory consumption.
- Optimize code, release unused resources, and manage memory effectively.
4. Integration with Performance Testing:
- LLM testing often integrates with overall performance testing:
- Performance Testing: Includes load, stress, scalability, and endurance testing.
- LLM Testing: Focuses on specific aspects related to load, latency, and memory.
- Together, they provide a comprehensive view of system performance.
Remember, effective LLM testing requires a combination of tools, monitoring, and analysis. Start by understanding your application's requirements and user expectations, and tailor your testing accordingly.
all the best..

[@janisheik3112]

Please share java script in Gatling. How to add the project in maven

[@RaghavPal]

I will check on this