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Load Testing using Locust.io (Open-source)

Mar 31, 2024

Locust is an open-source load testing tool written in Python. It allows you to simulate thousands of concurrent users and measure the performance of your application or system under load.

Here's a step-by-step guide on how to use Locust for load testing:

1) Install Locust

Locust can be installed using pip, the package manager for Python. Open a terminal or command prompt and run the following command:

pip install locust


pip3 install locust

2) Create a Locust file

Locust uses Python code to define the load testing scenarios. Create a new Python file, e.g., codeburps-load-test.py.

In Locust, users are simulated as classes. Create a class that inherits from HttpUser. Define the tasks that the user will perform using the task decorator.

3) Run Locust

Save the file and run it from the terminal or command prompt:

locust -f ~/code/locust/codeburps-load-test.py


~/Library/Python/3.9/bin/locust -f ~/code/locust/codeburps-load-test.py

4) Access the Locust web interface

After starting Locust, it will provide a web interface where you can configure the number of users and spawn rate, monitor the progress, and view various statistics.

Open a web browser and go to http://localhost:8089 (by default) to access the Locust web interface.

In the Locust web interface, set the number of total users, hatch rate (number of users to spawn per second), and other relevant settings.

Click the "Start swarming" button in the web interface to begin the load test. Locust will start spawning users and executing the defined tasks.

5) Monitor and analyze

The web interface provides real-time statistics about the current load test, including the number of requests per second, response times, failure rates, and more.

You can monitor these metrics to understand how your application performs under different loads.


NK Chauhan

NK Chauhan is a Principal Software Engineer with one of the biggest E Commerce company in the World.

Chauhan has around 12 Yrs of experience with a focus on JVM based technologies and Big Data.

His hobbies include playing Cricket, Video Games and hanging with friends.

Spring Framework
Core Java
Java Concurrency