{"id":1014,"date":"2020-03-18T00:00:00","date_gmt":"2020-03-18T00:00:00","guid":{"rendered":"https:\/\/en.pingcap.com\/blog\/run-first-chaos-experiment-in-ten-minutes\/"},"modified":"2025-03-04T06:06:36","modified_gmt":"2025-03-04T14:06:36","slug":"run-first-chaos-experiment-in-ten-minutes","status":"publish","type":"post","link":"https:\/\/www.pingcap.com\/ko\/blog\/run-first-chaos-experiment-in-ten-minutes\/","title":{"rendered":"Run Your First Chaos Experiment in 10 Minutes"},"content":{"rendered":"

Chaos Engineering is a way to test a production software system’s robustness by simulating unusual or disruptive conditions. For many people, however, the transition from learning Chaos Engineering to practicing it on their own systems is daunting. It sounds like one of those big ideas that require a fully-equipped team to plan ahead. Well, it doesn’t have to be. To get started with chaos experimenting, you may be just one suitable platform away.<\/p>\n

Chaos Mesh<\/a> is an easy-to-use<\/strong>, open-source, cloud-native Chaos Engineering platform that orchestrates chaos in Kubernetes environments. This 10-minute tutorial will help you quickly get started with Chaos Engineering and run your first chaos experiment with Chaos Mesh.<\/p>\n

For more information about Chaos Mesh, refer to our previous article<\/a> or the chaos-mesh project<\/a> on GitHub.<\/p>\n

<\/span>A preview of our little experiment<\/span><\/h2>\n

Chaos experiments are similar to experiments we do in a science class. It’s perfectly fine to stimulate turbulent situations in a controlled environment. In our case here, we will be simulating network chaos on a small web application called web-show<\/a>. To visualize the chaos effect, web-show records the latency from its pod to the kube-controller pod (under the namespace of kube-system<\/code>) every 10 seconds.<\/p>\n

The following clip shows the process of installing Chaos Mesh, deploying web-show, and creating the chaos experiment within a few commands:<\/p>\n\"whole-process-of-chaos-experiment\"\n

The whole process of the chaos experiment<\/div>\n

Now it’s your turn! It’s time to get your hands dirty.<\/p>\n

<\/span>Let’s get started!<\/span><\/h2>\n

For our simple experiment, we use Kubernetes in the Docker (Kind<\/a>) for Kubernetes development. You can feel free to use Minikube<\/a> or any existing Kubernetes clusters to follow along.<\/p>\n

Prepare the environment<\/h3>\n

Before moving forward, make sure you have Git<\/a> \uadf8\ub9ac\uace0 Docker<\/a> installed on your local computer, with Docker up and running. For macOS, it’s recommended to allocate at least 6 CPU cores to Docker. For details, see Docker configuration for Mac<\/a>.<\/p>\n

    \n
  1. Get Chaos Mesh:\n
    git clone https:\/\/github.com\/chaos-mesh\/chaos-mesh.git\ncd chaos-mesh\/\n<\/code><\/pre>\n<\/li>\n
  2. Install Chaos Mesh with the install.sh<\/code> script:\n
    .\/install.sh --local kind\n<\/code><\/pre>\n
    install.sh<\/code> is an automated shell script that checks your environment, installs Kind, launches Kubernetes clusters locally, and deploys Chaos Mesh. To see the detailed description of install.sh<\/code>, you can include the --help<\/code> option.<\/p>\n
    Note:<\/strong><\/p>\n
    If your local computer cannot pull images from docker.io<\/code> \ub610\ub294 gcr.io<\/code>, use the local gcr.io mirror and execute .\/install.sh --local kind --docker-mirror<\/code> instead.<\/p><\/blockquote>\n<\/li>\n
  3. Set the system environment variable:\n
    source ~\/.bash_profile\n<\/code><\/pre>\n<\/li>\n<\/ol>\n
    Note:<\/strong><\/p>\n