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Kubernetes

Kubernetes is an open source container orchestration engine for Google, which supports automated deployment, large-scale scalability, and application containerization management. When deploying an application in a production environment, multiple instances of the application are usually deployed to load balance application requests.

In Kubernetes, we can create multiple containers and run an application instance in each container, and then manage, discover and access this group of application instances through the built-in load balancing policy, and these details do not need to be manually configured and processed by operation and maintenance personnel.

Node

A node is the smallest computing hardware unit in Kubernetes. It is a representation of a single machine in a cluster. In most production systems, nodes are likely to be physical machines in the data center or virtual machines hosted on cloud providers such as Google's cloud platform. However, don't let convention limit your imagination. In theory, you can make anything into a node.

Thinking of the machine as a "node" allows us to insert an abstraction layer. Now, instead of worrying about the unique features of any single machine, we can simply think of each machine as a set of CPU and RAM resources that can be used. In this way, any machine can replace any other machine in the Kubernetes cluster.

Rancher

Rancher is an open source enterprise container management platform. With Rancher, enterprises no longer have to use a series of open source software to build a container service platform from scratch. Rancher provides a full-stack container deployment and management platform for managing Docker and Kubernetes used in production environments.

When I first started my trip to Kubernetes, I was looking for a way to set up a local deployment environment. Many people often use minikube or microk8s, both of which are ideal for beginners to operate in a single-node cluster environment. But after I have learned the basics, these two are obviously not enough, and I need to look further for a platform that can run a local multi-node cluster and is more similar to the production environment. To this end, I looked up a lot of references, and finally I found Rancher Server. Next, I'll show you how I set up my local K8S multi-node cluster.

Prepare virtual machines for master nodes and worker nodes

The figure above shows the architecture of the cluster, one master node and three worker nodes. To try cross-node features such as using ingress controller for load balancing, session persistence, host affinity, and so on, this is the minimum configuration.

The installation of Rancher Server is not complicated, it is packaged as a docker image and can be run as a container. The basic configuration of a node is the docker CE daemon running on the Linux virtual machine. In this example, I chose to use Ubuntu 18.04 LTS (for specific node requirements, please refer to Rancher's official document: https://rancher.com/docs/rancher/v2.x/en/installation/requirements/). When I finished the first VM setting, I copied it directly into the other three. If your operation is the same as mine, you can refer to the following two tips:

Install the specified version of Docker: https://docs.docker.com/install/linux/docker-ce/ubuntu/

After the Clone virtual machine, change the Ubuntu hostname: https://linuxize.com/post/how-to-change-hostname-on-ubuntu-18-04/

In the end, all four nodes were started on my computer (i5Jing 24G RAM) and allocated the following resources.

Master nodes (2 core, 4G RAM, Ubuntu 18.04 + Docker CE 18.09) x 1

Worker nodes (2 core, 3G RAM, Ubuntu 18.04 + Docker CE 18.09) x 3

Start Rancher serversudo docker run-- restart=unless-stopped\-- p 81:80-p 44443 rancher/rancher on the master node

The above command starts the Rancher server container and runs it on the master node. By default, nginx ingress controller is embedded in the worker node and ports 80 and 443 are bound. So I published Rancger server to ports 81 and 444 or other ports to avoid port conflicts.

Complete the initial setup of Rancher server

First, launch the Rancher server console with the master node IP address and port 444, which requires an administrator password.

Next, verify that the worker node arrives at the URL of the Rancher server. Here, for convenience, I directly use the master node IP address as the URL. Once the initial setup is complete, Rancher server can add a new cluster.

Create a new K8S cluster and master node

Because I want to run a K8S cluster on a local virtual machine instead of in the cloud, select the "custom" option (that is, "From my own existing nodes" as described above), and then select "None" for the cloud provider option of the new cluster.

Copy and run the docker command on the ubuntu virtual machine to start the master node. A master node must have at least etcd and control. If you plan to create a single-node cluster, you need to select all three roles and change the command.

After running the docker command, the new node will be displayed on the Rancher Server console, it will take some time to configure this node, and once the configuration is complete, the state will change to active.

Create a worker node

For worker nodes, we only need to select the role "Worker" in the node option, and then copy and run the docker command on the Ubuntu virtual machine of the three worker nodes.

Finally, the multi-node cluster is ready on my computer.

Install kubectl tools to manage the new K8S cluster

The Kubernetes version of the new cluster is v1.14.6, which you can see in the screenshot above. To better match the kubectl tool version to the cluster, run the following command on the master node to install a specific version:

Curl-LO https://storage.googleapis.com/kubernetes-release/release/v1.14.6/bin/linux/amd64/kubectlchmod + x. / kubectlsudo mv. / kubectl / usr/local/bin/kubectl

The Kubectl tool requires a kubeconfig file to connect to the cluster, and the kubeconfig file for the new cluster can be found in the Rancher Server console.

Copy the above kubeconfig file and save it as ~ / .kube / config file. Kubectl can then get the cluster information.

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