Distributed Load Testing Using Kubernetes
This tutorial demonstrates how to conduct distributed load testing using Kubernetes and includes a sample web application, Docker image, and Kubernetes controllers/services. For more background refer to the Distributed Load Testing Using Kubernetes solution paper.
- Google Cloud Platform account
- Install and setup Google Cloud SDK
Note: when installing the Google Cloud SDK you will need to enable the following additional components:
App Engine Command Line Interface (Preview)
App Engine SDK for Python and PHP
Compute Engine Command Line Interface
Developer Preview gcloud Commands
gcloud Alpha Commands
gcloud app Python Extensions
Before continuing, you can also set your preferred zone and project:
$ gcloud config set compute/zone ZONE $ gcloud config set project PROJECT-ID
Deploy Web Application
sample-webapp folder contains a simple Google App Engine Python application as the "system under test". To deploy the application to your project use the
gcloud preview app deploy command.
$ gcloud preview app deploy sample-webapp/app.yaml --project=PROJECT-ID --set-default
Note: you will need the URL of the deployed sample web application when deploying the
Deploy Controllers and Services
Before deploying the
locust-worker controllers, update each to point to the location of your deployed sample web application. Set the
TARGET_HOST environment variable found in the
spec.template.spec.containers.env field to your sample web application URL.
- name: TARGET_HOST key: TARGET_HOST value: http://PROJECT-ID.appspot.com
Update Controller Docker Image (Optional)
locust-worker controllers are set to use the pre-built
locust-tasks Docker image, which has been uploaded to the Google Container Registry and is available at
gcr.io/cloud-solutions-images/locust-tasks. If you are interested in making changes and publishing a new Docker image, refer to the following steps.
First, install Docker on your platform. Once Docker is installed and you've made changes to the
Dockerfile, you can build, tag, and upload the image using the following steps:
$ docker build -t USERNAME/locust-tasks . $ docker tag USERNAME/locust-tasks gcr.io/PROJECT-ID/locust-tasks $ gcloud preview docker --project PROJECT-ID push gcr.io/PROJECT-ID/locust-tasks
Once the Docker image has been rebuilt and uploaded to the registry you will need to edit the controllers with your new image location. Specifically, the
spec.template.spec.containers.image field in each controller controls which Docker image to use.
If you uploaded your Docker image to the Google Container Registry:
If you uploaded your Docker image to the Docker Hub:
Note: the image location includes the
latest tag so that the image is pulled down every time a new Pod is launched. To use a Kubernetes-cached copy of the image, remove
:latest from the image location.
Deploy Kubernetes Cluster
First create the Google Container Engine cluster using the
gcloud command as shown below.
Note: This command defaults to creating a three node Kubernetes cluster (not counting the master) using the
n1-standard-1 machine type. Refer to the
gcloud alpha container clusters create documentation information on specifying a different cluster configuration.
$ gcloud alpha container clusters create CLUSTER-NAME
After a few minutes, you'll have a working Kubernetes cluster with three nodes (not counting the Kubernetes master). Next, configure your system to use the
$ kubectl config use-context gke_PROJECT-ID_ZONE_CLUSTER-NAME
Note: the output from the previous
gcloud cluster create command will contain the specific
kubectl config command to execute for your platform/project.
kubectl is setup, deploy the
$ kubectl create -f locust-master-controller.yaml
To confirm that the Replication Controller and Pod are created, run the following:
$ kubectl get rc $ kubectl get pods -l name=locust,role=master
Next, deploy the
$ kubectl create -f locust-master-service.yaml
This step will expose the Pod with an internal DNS name (
locust-master) and ports
5558. As part of this step, the
type: LoadBalancer directive in
locust-master-service.yaml will tell Google Container Engine to create a Google Compute Engine forwarding-rule from a publicly avaialble IP address to the
locust-master Pod. To view the newly created forwarding-rule, execute the following:
$ gcloud compute forwarding-rules list
$ kubectl create -f locust-worker-controller.yaml
locust-worker-controller is set to deploy 10
locust-worker Pods, to confirm they were deployed run the following:
$ kubectl get pods -l name=locust,role=worker
To scale the number of
locust-worker Pods, issue a replication controller
$ kubectl scale --replicas=20 replicationcontrollers locust-worker
To confirm that the Pods have launched and are ready, get the list of
$ kubectl get pods -l name=locust,role=worker
Note: depending on the desired number of
locust-worker Pods, the Kubernetes cluster may need to be launched with more than 3 compute engine nodes and may also need a machine type more powerful than n1-standard-1. Refer to the
gcloud alpha container clusters create documentation for more information.
Setup Firewall Rules
The final step in deploying these controllers and services is to allow traffic from your publicly accessible forwarding-rule IP address to the appropriate Container Engine instances.
The only traffic we need to allow externally is to the Locust web interface, running on the
locust-master Pod at port
8089. First, get the target tags for the nodes in your Kubernetes cluster using the output from
kubectl get nodes:
$ kubectl get nodes NAME LABELS STATUS gke-ws-0e365264-node-4pdw kubernetes.io/hostname=gke-ws-0e365264-node-4pdw Ready gke-ws-0e365264-node-jdcz kubernetes.io/hostname=gke-ws-0e365264-node-jdcz Ready gke-ws-0e365264-node-kp3d kubernetes.io/hostname=gke-ws-0e365264-node-kp3d Ready
The target tag is the node name prefix up to
-node and is formatted as
gke-CLUSTER-NAME-[...]-node. For example, if your node name is
gke-mycluster-12345678-node-abcd, the target tag would be
Now to create the firewall rule, execute the following:
$ gcloud compute firewall-rules create FIREWALL-RULE-NAME --allow=tcp:8089 --target-tags gke-CLUSTER-NAME-[...]-node
To execute the Locust tests, navigate to the IP address of your forwarding-rule (see above) and port
8089 and enter the number of clients to spawn and the client hatch rate then start the simulation.
To teardown the workload simulation cluster, use the following steps. First, delete the Kubernetes cluster:
$ gcloud alpha container clusters delete CLUSTER-NAME
Next, delete the forwarding rule that forwards traffic into the cluster.
$ gcloud compute forwarding-rules delete FORWARDING-RULE-NAME
Finally, delete the firewall rule that allows incoming traffic to the cluster.
$ gcloud compute firewall-rules delete FIREWALL-RULE-NAME
To delete the sample web application, visit the Google Cloud Console.
This code is Apache 2.0 licensed and more information can be found in
LICENSE. For information on licenses for third party software and libraries, refer to the