Top 10 JMeter questions to ask ChatGPT

In my last post, we explored ChatGPT use cases for performance engineers. We touched upon many aspects of performance engineering starting from explaining performance testing to a six-year-old kid to build a performance testing tool. The ChatGPT response was insane. In this article, we are going to ask the top 10 JMeter questions to ask ChatGPT.

ChatGPT Use Cases for Performance Engineers

Download and Install JMeter

Let us start with the basics. Here is the ChatGPT response on how to download and install JMeter on Windows and Linux operating systems.

ChatGPT’s response

To download and install Apache JMeter on a Windows operating system, follow these steps:

  1. Go to the Apache JMeter website (http://jmeter.apache.org/) and click on the “Download” button.
  2. Scroll down to the “Binary Releases” section and download the latest version of Apache JMeter for Windows.
  3. Once the download is complete, open the .zip file and extract the contents to a location on your computer.
  4. Open the extracted folder and double-click on the “ApacheJMeter.jar” file to launch the application.

To download and install Apache JMeter on a Linux operating system, follow these steps:

  1. Go to the Apache JMeter website (http://jmeter.apache.org/) and click on the “Download” button.
  2. Scroll down to the “Binary Releases” section and download the latest version of Apache JMeter for Linux.
  3. Once the download is complete, open the terminal and navigate to the directory where the downloaded file is located.
  4. Use the command: tar -xzf apache-jmeter-x.x.x.tgz to extract the contents of the downloaded file.
  5. Navigate to the extracted folder and use the command: ./bin/jmeter to launch the application.

Make sure to replace x.x.x with the version number of the downloaded file.

Well, that was neat. But it missed a step to check the integrity of the downloaded file.

Recording mobile traffic in JMeter

Let us ask ChatGPT on how to record mobile traffic in JMeter.

ChatGPT’s response:

Recording mobile traffic in JMeter involves the following steps:

  1. Start the JMeter application on your computer.
  2. In the JMeter menu, select “File” > “Templates” > “Recording” to open the HTTP(S) Test Script Recorder.
  3. Configure your mobile device to use the computer as a proxy. To do this, go to your mobile device’s settings and navigate to the “Wi-Fi” or “Network” settings. Find the option to configure a proxy and enter the IP address of your computer and the port number that the JMeter recorder is using (default is 8888).
  4. In the JMeter recorder, click the “Start” button to begin recording.
  5. Use your mobile device to navigate to the website or application that you want to record. All of the requests and responses will be captured by the JMeter recorder.
  6. When you are finished recording, click the “Stop” button in the JMeter recorder.
  7. The recorded traffic will be displayed in the JMeter interface as a series of HTTP Request samplers. You can edit and configure these samplers as needed, and then use them to create a test plan for your mobile application.

Note: In case, you are using a mobile device that is connected to a cellular network, you will need to forward the traffic through a VPN tunnel, because the mobile device needs to connect to the computer via the same network.

Excellent response. It even touched upon the VPN tunnel.

Design a MongoDB database test plan

Let us ask ChatGPT to design a MongoDB database test plan.

ChatGPT’s response

  1. Firstly, install MongoDB on your computer and create a new database that you will use for testing.
  2. Next, install the MongoDB plugin for JMeter (if it is not already installed) by navigating to “Options” > “Plugins Manager” and searching for the MongoDB plugin.
  3. Create a new test plan in JMeter and add a “Thread Group” element to it. This will allow you to specify the number of concurrent users that will be accessing the database during the test.
  4. Add a “MongoDB Script” element to the thread group. In this element, specify the connection details for the MongoDB database, including the hostname, port, and database name.
  5. Next, add a “MongoDB Read Sampler” element to the thread group. This element will allow you to specify a query for the MongoDB database, such as a specific collection or document.
  6. In the “MongoDB Read Sampler,” specify the query that you want to use to retrieve data from the database. For example, you can retrieve all documents from a specific collection.
  7. Add a “View Results Tree” listener to the thread group to view the results of the query in real-time.
  8. Once the test plan is set up, run the test by clicking the “Start” button in the JMeter interface. The test will send a specified number of queries to the MongoDB database and retrieve the results.
  9. After the test is complete, analyze the results in the “View Results Tree” listener and make note of any errors or performance issues.
  10. Use the results to identify and troubleshoot any issues in your MongoDB database or application.

Note: You can also add a “MongoDB Write Sampler” element to the thread group, to test the write performance of the database by inserting and updating the data, in addition to read performance.

Not bad, it provided a high level of instruction. But it is still helpful.

Generate runtime settings for load testing, stress testing, and endurance testing

Let us ask ChatGPT to generate runtime settings for load testing, stress testing, and endurance testing with examples.

ChatGPT’s response

Load Testing:

  • Number of concurrent users: 50-100
  • Ramp-up period: 60 seconds
  • Loop count: 1-2
  • Think time: 5 seconds

Example: A load test for a website that simulates 50 concurrent users accessing the site over a 60-second ramp-up period, with a loop count of 1 and a think time of 5 seconds between each request. This test will help to identify any bottlenecks or performance issues when the website is under normal to moderate load.

Stress Testing:

  • Number of concurrent users: 150-200
  • Ramp-up period: 30 seconds
  • Loop count: 2-3
  • Think time: 2 seconds

Example: A stress test for a website that simulates 150 concurrent users accessing the site over a 30-second ramp-up period, with a loop count of 2 and a think time of 2 seconds between each request. This test will help to identify the breaking point of the website and identify any bottlenecks or performance issues when the website is under heavy load.

Endurance Testing:

  • Number of concurrent users: 50-100
  • Ramp-up period: 60 seconds
  • Loop count: 1
  • Think time: 5 seconds
  • Duration: 24 hours

Example: An endurance test for a website that simulates 50 concurrent users accessing the site over a 60-second ramp-up period, with a loop count of 1, a think time of 5 seconds between each request and running the test for 24 hours. This test will help to identify any performance issues or memory leaks that may occur over a longer period of time.

Wow. Note the tool specific terms, duration, ramp-up, and more. I hope now you know the difference between load, stress, and endurance testing.

Generate test data

Let us ask ChatGPT to generate 10 sample test data for a shopping cart in a CSV format.

ChatGPT’s response

Item Name, Item Quantity, Item Price
"Shampoo", "2", "5.99"
"Conditioner", "1", "6.99"
"Toothpaste", "3", "2.99"
"Body wash", "1", "8.99"
"Laundry detergent", "2", "9.99"
"Paper towels", "6", "3.99"
"Hand soap", "1", "4.99"
"Toilet cleaner", "1", "5.99"
"All-purpose cleaner", "1", "6.99"

Note: the format is Item Name, Item Quantity, Item Price, you can add more columns as needed like Item description, Item brand, Item category, etc.

That was so cool. We need to just copy and paste to save it as CSV. Wish, ChatGPT has a download button to download raw data :)

Data Parameterization

Let us ask ChatGPT to parameterize above test data in JMeter.

ChatGPT’s response

To use the above test data in JMeter, you can follow these steps:

  1. In JMeter, create a new Test Plan and add a Thread Group to it.
  2. Under the Thread Group, add a CSV Data Set Config element, which allows you to read data from a CSV file.
  3. In the CSV Data Set Config element, specify the file path of the CSV file that contains your test data.
  4. In the same element, specify the variable names that will be used in the test to reference the values in the CSV file. For example, you can use “itemName” to reference the item name, “itemQuantity” to reference the item quantity, and “itemPrice” to reference the item price.
  5. Under the CSV Data Set Config element, add an HTTP Request element, which will be used to send the data to the server.
  6. In the HTTP Request element, specify the server URL and the HTTP method (GET or POST) that you want to use to send the data.
  7. In the HTTP Request element, you can use the variable names that you specified in the CSV Data Set Config to reference the values in the CSV file. For example, you can use ${itemName} to reference the item name, ${itemQuantity} to reference the item quantity, and ${itemPrice} to reference the item price.
  8. Add a “View Results Tree” listener to the Thread Group to view the results of the test in real-time.
  9. Once the test plan is set up, run the test by clicking the “Start” button in the JMeter interface. The test will use the test data from the CSV file to send requests to the server and retrieve the results.
  10. After the test is complete, analyze the results in the “View Results Tree” listener and make note of any errors or performance issues.

Note: you can use different elements like Assertions and Listeners to check if the responses received are as expected and to check the performance of the application.

It even associated the test data column in the above instructions. Kudos.

Generate JSON payload in Groovy

Let us get into Groovy scripting. Let us ask ChatGPT to write a groovy script to generate a payload with the shopping cart data.

ChatGPT’s response

Here is a sample Groovy script that you can use to generate the payload in JSON format in JMeter:

def itemName = vars.get("itemName")
def itemQuantity = vars.get("itemQuantity")
def itemPrice = vars.get("itemPrice")

// calculate total cart value
def totalCart = itemQuantity * itemPrice

// create JSON object
def json = new groovy.json.JsonBuilder()
json {
    itemName itemName
    itemQuantity itemQuantity
    itemPrice itemPrice
    totalCart totalCart
}

// set JSON payload as a variable
vars.put("payload", json.toString())

You can add this script as a JSR223 PreProcessor element in your thread group and reference the variable “payload” in your HTTP request element to send the JSON payload in the request body.

Note: you should install groovy plugin in order to use groovy.json.JsonBuilder class, if it is not already installed.

Above snippet will not work :). Here is the working code.

import groovy.json.*

def itemName = vars.get("itemName")
def itemQuantity = vars.get("itemQuantity")
def itemPrice = vars.get("itemPrice")

// calculate total cart value
def totalCart = itemQuantity * itemPrice

// create JSON object
JsonBuilder json = new JsonBuilder()
json{
    name itemName
    quantity itemQuantity
    price itemPrice
    total totalCart
}

// set JSON payload as a variable
vars.put("payload", json.toString())

I have already shared the feedback with ChatGPT.

Distributed mode in JMeter on EC2

It is time to run our test in distributed fashion on AWS EC2.

ChatGPT’s response

Running JMeter in distributed mode on EC2 involves the following steps:

  1. Start by creating an EC2 instance on Amazon Web Services (AWS) and install JMeter on it. This instance will be used as the master node.
  2. Create additional EC2 instances and install JMeter on them as well. These instances will be used as the slave nodes.
  3. Configure the master node by editing the jmeter.properties file located in the /bin directory. In the file, set the remote_hosts property to the IP addresses of the slave nodes, separated by commas.
  4. On the master node, navigate to the /bin directory and run the command:
jmeter -n -t [test_plan.jmx] -r -l [results_file.jtl]
  1. On each of the slave nodes, navigate to the /bin directory and run the command:
jmeter-server
  1. Once the test is complete, the results will be collected on the master node and can be viewed using the JMeter GUI or analyzed using a tool such as the “View Results Tree” listener.

Note: You should make sure that the firewall is open to the IP address of the master node on the slave nodes and vice versa, to make sure the communication is established properly. Also, when you use more than one slave node, you should make sure to balance the load between them as well as to match the resources of each slave node with the expected loads.

I did not test the above instructions. It used the terms master and slave which is not appropriate. Overall, the instructions were satisfactory; it missed a few steps though.

Monitor system resources

Let us ask ChatGPT to monitor CPU, memory, disk and network utilization.

ChatGPT’s response

There are several ways to monitor the CPU, memory, disk, and network usage in JMeter:

  1. Using the built-in JMeter listeners:
  • “Summary Report” listener provides information about the average response time, throughput, and error rate.
  • “Graph Results” listener displays a graph of the response times and throughput over time.
  • “PerfMon” listener allows you to monitor system resources such as CPU, memory, and disk usage on the local machine or remote machines.
  1. Using the JMeter Plugins: The JMeter Plugins provide additional listeners and samplers that can be used to monitor system resources such as CPU, memory, and disk usage. For example, the “PerfMon Agent” plugin can be used to monitor the system resources on the local machine or remote machines.
  2. Using external monitoring tools: You can use external monitoring tools such as “Grafana” and “InfluxDB” to monitor the system resources on the main machine and worker machines. These tools collect the system metrics and display them in a graphical format.
  3. Using AWS CloudWatch: You can use AWS CloudWatch to monitor the EC2 instances and track the system resources such as CPU, memory, disk and network.

In addition, you can use the JMX monitoring to monitor the JVM resources of the instances, also you can use an APM tool like New Relic, AppDynamics, etc to get more insights on your application and infrastructure performance.

The response is generic and targeted AWS as our previous question was about AWS. It listed commonly used tools such as Grafana, InfluxDB, New Relic and more.

CI/CD

Let us ask ChatGPT to run JMeter on Jenkins.

ChatGPT’s response

Running JMeter scripts in Jenkins pipeline involves the following steps:

  1. Create a Jenkins pipeline job and configure it to use a Jenkinsfile for the pipeline definition.
  2. In the Jenkinsfile, define the stages for the pipeline. One of the stages should be dedicated to running the JMeter test script.
  3. In the Jenkinsfile, install the “Performance Plugin” and “JMeter” plugins to allow Jenkins to run the JMeter test script.
  4. In the Jenkinsfile, use the “performance” step to run the JMeter test script. The step takes the path to the JMeter test script as an argument. For example:
performance 'path/to/test.jmx'
  1. In the Jenkinsfile, use the “performancePublisher” step to publish the test results. For example:
performancePublisher(fileIncludePattern: '**/*.jtl', ignoreFailure: true)
  1. Save the Jenkinsfile and run the pipeline job. The pipeline will run the stages defined in the Jenkinsfile, including the stage for running the JMeter test script.
  2. Once the pipeline is completed, the test results will be published and can be viewed in the Jenkins UI.

Note: you should also configure the environment in Jenkins by installing the JMeter in the Jenkins machine and setting the JAVA_HOME and JMETER_HOME variables.

Also, you should make sure that the performance plugin is installed and configured in Jenkins, and make sure that the path of the test plan file is correct and accessible by Jenkins.

This is a cool response. It even touched configuring Java.

Final Thoughts

Overall ChatGPT’s response is definitely great. But there is a lot of room for improvement. You can use ChatGPT to write simple snippets, code review, general instructions, tips, and tricks and more. But it cannot replace engineers or testers at least for the next few years. It is important to note that Google and ChatGPT are not the same.

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