LOAD_TESTING.md

Load Testing with Locust

Load testing is a key component of API development, and Locust is an easy-to-learn tool that employs Python scripts to "swarm" services. It consumes less local resources than most competing tools and has a clean UI via browser interface. This guide will walk you through the setup and sample loadtesting scenarios for Platform projects.

Installation

1. Install pip:

curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py
...
python3 get-pip.py

2. If you encounter the following warning:

WARNING: The scripts pip, pip3 and pip3.8 are installed in '/Users/Will/Library/Python/3.8/bin' which is not on PATH.
Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
NOTE: The current PATH contains path(s) starting with `~`, which may not be expanded by all applications.

• sudo nano /etc/paths
• Add the directory from the previous command.
• Save the file and exit.
• Restart Terminal.

3. In Terminal, navigate to {project}/Tests.

4. Copy the following content into locustfile.py:

from locust import HttpUser, task
import uuid

class ServiceUser(HttpUser):
# 	wait_space = between(1, 5)

	@task(1)
	def hello_world(self):
		self.client.get("{base}/health", name="/health")

Note: Replace {base} with your service path.

Start Locust processes

Python has a limitation in that it can't run more than one core per process. However, Locust has the ability to use worker processes to increase its load. This is an important factor in nuking services.

1. In your main Terminal tab, run the command locust -f locustfile.py --master.

2. For each worker process, open a new Terminal tab and run the command locust -f locustfile.py --worker

Each worker process will increase your requests per second (up to the number of cores in your machine). It's recommended to have at least 4 worker processes.

3. In your browser, navigate to localhost:8089, then click "New test" in the upper right corner.

4. Enter the number of Locust workers as your number of users and http://localhost:{port}, where {port} is your service's assigned port number.