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Scaling Performance Testing with Kubernetes and k6: Leveraging Containerization for Distributed Load Generation

Sujeet Kumar Srivastava
Sujeet Kumar Srivastava
Table of Contents

Performance testing plays a pivotal role in ensuring the smooth functioning of software applications under varying loads. Traditional performance testing tools often struggle to cope with the dynamic nature of modern, containerized applications. Kubernetes, a popular container orchestration platform, offers a scalable and adaptable environment for performance testing.

Scaling Performance Testing with Kubernetes

In this blog post, we will explore how to scale performance testing using Kubernetes and k6, a modern load testing tool, to leverage containerization for distributed load generation.some more complex and user traffic increases, it’s essential to have a robust strategy for evaluating how your system behaves under various loads.

Why Kubernetes and k6?

Before delving into the technical details, let’s first understand why Kubernetes and k6 are a compelling combination for scaling performance testing:

Kubernetes is a popular container orchestration platform that enables you to manage and scale your containerized applications easily. k6, on the other hand, is an open-source load testing tool built for scalability and flexibility. Combining these two tools allows you to scale your performance testing infrastructure effortlessly, simulate real-world scenarios, and gather meaningful insights into your application’s performance.


  • Scalability: Kubernetes excels at managing containers at scale, making it ideal for load testing where rapid scaling is required to simulate diverse loads.
  • Isolation: Each test instance can run within a dedicated container, ensuring that one test does not interfere with another, thereby replicating real-world scenarios accurately.
  • Orchestration: Kubernetes simplifies the deployment and management of containerized applications, including load generators. It automates container scaling, load balancing, and updates, streamlining the testing process.


  • Modern and Open-Source: k6 is a popular open-source load testing tool designed for modern applications. It supports scripting using JavaScript and provides real-time insights into test results.
  • Container-Friendly: k6 is lightweight and container-friendly, making it easy to run within containers on Kubernetes.
  • Distributed Testing: k6 supports distributed load testing, enabling you to generate high loads by orchestrating multiple k6 instances simultaneously.

Now, let’s dive into how to harness these tools for scaling your performance testing efforts.


  • A Kubernetes cluster up and running.
  • kubectl should be installed and configured to communicate with your cluster.
  • Docker installed on your local machine for building custom k6 Docker images.
  • Performance Testing Scripts: Create performance testing scripts using k6.

1. Write your K6 Performance Test Script

import { check } from 'k6';
import http from 'k6/http';

export const options = {
    vus: 50,
    duration: '10s',

export default function () {
  const res = http.get('');
  check(res, {
    'is status 200': (r) => r.status === 200,

2. Setting up a Kubernetes Deployment

Let’s start by creating a Kubernetes Deployment that will run our k6 load tests. Save your k6 test script as test.js and create a Dockerfile for building a custom k6 Docker image:

FROM loadimpact/k6

COPY test.js /test.js

CMD ["run", "/test.js"]

This Dockerfile is minimal but allows you to package your k6 script into a container. You can modify it according to your requirements. Build the image and push it to a container registry if necessary.

3. Build the Docker image

Build the Docker image using below command:

docker build -t my-k6-test .

This command builds the Docker image based on the Dockerfile and tags it as k6-tests. The -t option is used to tag the Docker image with a name (my-k6-test in this example). The . at the end indicates that the Dockerfile is in the current directory.
Once the image is built, you can push it to a container registry if needed.

4. Deploying k6 Containers on Kubernetes

With our containerized k6 scripts ready, we can deploy them as pods on a Kubernetes cluster. Here’s a simplified YAML manifest to create a Kubernetes deployment for load testing:

apiVersion: apps/v1
kind: Deployment
  name: k6-deployment
  replicas: 5
      app: k6
        app: k6
        - name: k6
          image: my-k6-test:latest
          command: ["k6", "run", "--vus", "10", "--duration", "30s", "/test.js"]

In this YAML file, we define a Deployment with 5 replicas, each running a k6 container with the custom image. Adjust the –vus (virtual users) and –duration flags to suit your testing needs.
In this example, we’ve created a deployment with five replicas to simulate concurrent users. Adjust the replicas value based on your testing requirements. The command field specifies the k6 command to run your script. Make sure to replace your-registry and your-k6-image with the appropriate image details.

5. Apply the Deployment to your Kubernetes cluster:

kubectl apply -f k6-deployment.yaml

Kubernetes will schedule the k6 pods to run the performance tests. You can monitor the progress using kubectl logs or retrieve the results from the k6 pods.

6. Running the Tests

With the Deployment in place, the k6 tests will be automatically executed in parallel by the specified number of replicas. To monitor the test progress and results, you can set up Grafana and Prometheus for visualization and monitoring.

7. Gathering and Analyzing Results

k6 provides various output options, including JSON, which is suitable for automated performance testing. To output results in JSON, add the –out json=/data/results.json flag to your k6 command.

Once the test is complete, collect the result files from the k6 pods and analyze them using tools like Grafana, InfluxDB, or even a simple script to extract performance metrics. You can set up data visualization dashboards to gain insights into your application’s performance characteristics.

8. Scaling the Tests

One of the significant advantages of using Kubernetes is the ease of scaling the performance testing. If you need to scale your performance tests further, simply update the number of replicas in the Deployment. For example, to double the testing load, you can change the replicas field from 5 to 10 in the Deployment YAML and apply the changes.

  replicas: 10

Kubernetes will take care of scaling the tests horizontally by adding more pods.

Scaling performance testing with Kubernetes and k6 offers an efficient way to ensure your web applications can handle the expected load. By defining your tests as code, you can easily scale the testing infrastructure up or down to meet your specific requirements. Kubernetes’ orchestration capabilities make it an ideal choice for managing containers and running distributed performance tests.


Sujeet Kumar Srivastava

Sujeet Kumar Srivastava

I am a seasoned automation testing professional having sound knowledge of automation testing methodologies and tools. I have good understanding in designing and implementing test frameworks, creating test plans, and executing automated tests across multiple platforms and devices. I am always charged up for picking up & learning new things. On a personal front, I am fitness enthusiast and loves to play volleyball.

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