Md Imran

Posted on Oct 12

Introducing k8s-pod-cpu-stressor: Simplify CPU Load Testing in Kubernetes

#kubernetes #devops #cloudcomputing #performance

I created k8s-pod-cpu-stressor because there are times during development or testing when we need a simple way to generate CPU utilization within Kubernetes. Whether you're a developer, a DevOps engineer, or someone managing Kubernetes infrastructure, this tool makes it easy to simulate various CPU loads and understand how your system reacts under pressure. In this article, I'll walk you through the benefits of k8s-pod-cpu-stressor, how it can be used for testing, and the step-by-step guide on getting started.

Oh, and by the way, if you think this tool sounds awesome, why not give it a star on GitHub? ⭐️ Your support means a lot!

Also, the Docker image is ready for you! Head over to Docker Hub and start playing around with it!

Why Do We Need CPU Stress Testing?

In Kubernetes, managing resource utilization is key to ensuring the stability and reliability of your applications. There are many scenarios where simulating CPU usage is useful:

Development Testing: You might need to understand how your application behaves under different levels of CPU load during development.
Scaling and Autoscaling: Verifying your Horizontal Pod Autoscaler (HPA) settings by creating controlled CPU usage scenarios.
Performance Optimization: Identifying the CPU bottlenecks in your applications.
Chaos Engineering: Ensuring that your system is resilient to unpredictable CPU spikes.

The k8s-pod-cpu-stressor was designed to be easy to use, configurable, and lightweight, making it a great option for all of these use cases.

What is k8s-pod-cpu-stressor?

The k8s-pod-cpu-stressor is a simple, effective tool for generating controlled CPU load on Kubernetes pods. With a few configurable options, you can specify the desired CPU usage percentage, set stress duration, or even run it indefinitely. This makes it highly versatile for different testing purposes, including validating auto-scaling behavior and assessing cluster resilience.

Key Features

Configurable CPU Usage: Specify the CPU utilization as a fraction of the total CPU available (e.g., 0.2 for 20% usage).
Flexible Duration: Define how long the stress test runs, from a few seconds to several hours.
Run Indefinitely: Use the -forever argument to run the CPU stress continuously until manually stopped. This is useful for long-running performance and resilience testing.
Lightweight and Easy to Deploy: Build it with Go, deploy it with Docker or Kubernetes—no complicated dependencies.

How to Use k8s-pod-cpu-stressor

Prerequisites

To use k8s-pod-cpu-stressor, you will need:

Go (version 1.19 or higher)
Docker

Building the Binary

To get started, clone the GitHub repository and build the binary:

# Clone the repository
git clone https://github.com/narmidm/k8s-pod-cpu-stressor.git
cd k8s-pod-cpu-stressor

# Build the binary
go build -o cpu-stress .

Once you've built the binary, you can run it locally or create a Docker container.

Running with Docker

You can use Docker to build a container and run it:

# Build the Docker image
docker build -t k8s-pod-cpu-stressor .

# Run the container with the desired CPU usage and duration
docker run --rm k8s-pod-cpu-stressor -cpu=0.5 -duration=30s -forever

Replace 0.5 with the fraction of CPU you want to utilize (e.g., 50%), and 30s with the desired duration. Alternatively, you can add the -forever flag to run the stressor indefinitely.

Deploying k8s-pod-cpu-stressor in Kubernetes

The real power of k8s-pod-cpu-stressor is in deploying it within a Kubernetes cluster. Here's how to get started:

Sample Deployment Manifest

apiVersion: apps/v1
kind: Deployment
metadata:
  name: cpu-stressor-deployment
spec:
  replicas: 1
  selector:
    matchLabels:
      app: cpu-stressor
  template:
    metadata:
      labels:
        app: cpu-stressor
    spec:
      containers:
        - name: cpu-stressor
          image: narmidm/k8s-pod-cpu-stressor:latest
          args:
            - "-cpu=0.2"
            - "-duration=60s"
            - "-forever"
          resources:
            requests:
              cpu: "100m"
            limits:
              cpu: "200m"

This configuration will run the stressor at 20% CPU utilization for 60 seconds, with resource requests and limits defined to keep things under control.

Using Kubernetes Jobs for One-Time Stress Testing

For scenarios where you need a one-time stress test, you can use a Kubernetes Job. Jobs are perfect for running tasks that need to complete and then stop.

Here's an example manifest for a Kubernetes Job:

apiVersion: batch/v1
kind: Job
metadata:
  name: cpu-stressor-job
spec:
  template:
    metadata:
      labels:
        app: cpu-stressor
    spec:
      containers:
        - name: cpu-stressor
          image: narmidm/k8s-pod-cpu-stressor:latest
          args:
            - "-cpu=0.4"
            - "-duration=5m"
            - "-forever"
          resources:
            requests:
              cpu: "250m"
            limits:
              cpu: "500m"
      restartPolicy: Never
  backoffLimit: 3

This job will run a stress test at 40% CPU load for 5 minutes, which is great for testing how well your cluster handles sudden CPU spikes.

Benefits of Using k8s-pod-cpu-stressor

1. Development and Testing Made Easier

k8s-pod-cpu-stressor simplifies testing scenarios where CPU usage is a critical factor. Developers can see how their applications behave when resources are constrained, making it easier to identify potential bottlenecks.

2. Validate Autoscaling Mechanisms

With k8s-pod-cpu-stressor, you can simulate load and validate your cluster's autoscaling policies. This helps ensure that Kubernetes is scaling your pods appropriately based on CPU usage.

3. Optimize Resource Requests and Limits

By understanding how your application behaves under stress, you can adjust Kubernetes resource requests and limits to optimize performance. This can lead to better utilization of cluster resources, avoiding both under- and over-provisioning.

4. Strengthen System Resilience

Stress testing with this tool helps identify weak points in your cluster, improving its resilience. By proactively testing how your system reacts to different CPU loads, you can ensure that it handles real-world traffic and demand fluctuations gracefully.

Best Practices for k8s-pod-cpu-stressor

Start in a Non-Production Environment: Always begin stress testing in a safe environment. This ensures that unexpected outcomes do not affect your users.
Monitor with Metrics Tools: Use monitoring tools like Prometheus, Grafana, or the Kubernetes metrics-server to track resource usage and observe the impact of CPU stress testing.
Gradual Increase in Load: Start with lower CPU usage and incrementally increase it to identify the breaking point without overwhelming your system all at once.
Resource Limits: Always define requests and limits to prevent a runaway pod from affecting other applications.

Conclusion

k8s-pod-cpu-stressor is a practical, easy-to-use tool that can make CPU load testing in Kubernetes simple and accessible for developers and DevOps engineers alike. Whether you're validating autoscaling policies, optimizing resource requests, or simply exploring how your app behaves under load, this tool can help you create realistic CPU stress scenarios.

If you are looking to improve your Kubernetes setup, I highly recommend trying out k8s-pod-cpu-stressor. It's lightweight, flexible, and incredibly useful for development, testing, and ensuring that your cluster can handle the unexpected.

Give it a try and let me know how it works for you! Feel free to share your experiences or suggest improvements—I’d love to collaborate further on making Kubernetes stress testing as effective as possible.

Happy testing and scaling!

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