The code for the manifest script can be found here

Every single time I need to run some load testing, I'm faced with analysis paralysis syndrome.

So after searching I bumped into locust.io, a python based distributed load testing framework.

I'm not a Python developer, but locust is simple enough that made me reconsider dumping gatling and give it a try. FWIW: Gatling is extremely powerful, but also quite more complex to work with.

Ok, time to wrap this on a container and run on kubernetes, luckily someone already did that: Distributed load testing using Kubernetes

But I was not ok with that solution, mostly because I had to build a new container for every test. The flow I was considering was a bit more like this:

1. Tests are saved to github
2. Images are immutable
3. Users create clusters and point to a specific test

The good thing is that achieving this is relatively easy, we can add an Init Container section to pull the tests from github:

 initContainers:
      - name: gitbox
        image: viniciusccarvalho/alpine-git
        command:
        - git
        - clone
        - "https://github.com/user/test-repository"
        - "/data/tests"
        volumeMounts:
        - name: workdir
          mountPath: "/data/"

So now when the locust container starts all the test resources should be available at the /data/ folder.

Automate all the things

To deploy a locust cluster we will need 4 kubernetes resources:

1. A master deployment
2. A worker deployment (with N number of replicas and pointing to the master service)
3. A master service (using ClusterIp so workers can access the master)
4. A Loadbalancer service for the master (optional) for accessing the endpoint

All those files would only differ on a few parts (the repo, the target file, the target host, and the name), so I decided to create a script that automatically creates those files.

You can pull it here

If you run the script with a -h you would get all the required parameters to create the artifacts:

python locust-deploy.py -h
usage: locust-deploy.py [-h] -n NAME -t TARGET_HOST -r REPO -f TEST_FILE
                        [-s SIZE] [-o OUTPUT]

Locust cluster manifest generator

optional arguments:
  -h, --help            show this help message and exit
  -n NAME, --name NAME  Name of the test cluster artifacts
  -t TARGET_HOST, --target_host TARGET_HOST
                        Target host to run tests against
  -r REPO, --repo REPO  Github repository containing the tests
  -f TEST_FILE, --test_file TEST_FILE
                        The locust file to be used, relative to the github
                        root path
  -s SIZE, --size SIZE  Number of workers pods to be created. Default to 1
  -o OUTPUT, --output OUTPUT
                        Manifest files output

And if you run it pointing to a location, say ~/tmp/locust-deployments you end up with:

 ls -la ~/tmp/locust-deployments
total 32
drwxr-xr-x   6 vinnyc  primarygroup   192 Oct 16 17:45 .
drwxr-xr-x  16 vinnyc  primarygroup   512 Oct 16 11:35 ..
-rw-r--r--   1 vinnyc  primarygroup   246 Oct 16 17:45 appengine-locust-master-service-lb.yaml
-rw-r--r--   1 vinnyc  primarygroup   352 Oct 16 17:45 appengine-locust-master-service.yaml
-rw-r--r--   1 vinnyc  primarygroup  1415 Oct 16 17:45 appengine-locust-master.yaml
-rw-r--r--   1 vinnyc  primarygroup  1285 Oct 16 17:45 appengine-locust-worker.yaml

After deploying those artifacts you will have a new locust cluster ready to be accessed on your LB public endpoint:

There you have it, a very simple, and easy to deploy 20 node swarm test cluster for you to use.

Happy coding