Kubernetes fundamentals and setup multi-node kubernetes cluster using Google Kubernetes Engine(GKE)

What is Kubernetes?

Kubernetes is an open-source software system that allows you to easily deploy and manage containerized applications and services.

  • It relies on the features of Linux containers to run heterogeneous applications without knowing any internal details of these applications and without having to manually deploy these applications on each host.
  • Kubernetes enables us to run our software applications on thousands of computer nodes as if all those nodes were a single, enormous computer. Kubernetes exposes the whole data-center as a single deployment platform.
  • Deploying applications through Kubernetes is always the same, whether your cluster contains only a couple of nodes or thousands of them. The size of the cluster makes no difference at all. 
  • Kubernetes can be thought of as an operating system for the cluster.

Bird’s-eye view of Kubernetes:

  • A system is composed of a master node and any number of worker nodes. 
  • When the developer submits a list of apps to the master, Kubernetes deploys them to the cluster of worker nodes. 
  • It does not really matter where apps are deployed(on which worker nodes) unless developer specify specify that certain apps must run together and Kubernetes will deploy them on the same worker node.  

Kubernetes exposes the whole datacenter as a single deployment platform.

How Kubernetes helps developer and Ops team?

  • Kubernetes provides infrastructure-related service, developer does not need to implement certain infrastructure-related services(like service discovery, scaling, load-balancing, self-healing, and even leader election) into their apps; instead they rely on Kubernetes to provide these services.
  • Kubernetes will run your containerized app somewhere in the cluster,it helps to achieve far better resource utilization than is possible with manual scheduling by ops team.

Kubernetes cluster components

  • At high level Kubernetes cluster is made up of Master(Control Plane) and worker nodes. 
  • Control Plane controls the cluster and anchors its functioning. It consists of multiple components that can run on a single master node or be split across multiple nodes and replicated to ensure high availability. Control plane consist of following components:
    1. Kubernetes API Server: It act as single point of interaction, submit add descriptor by developer and interact with another control place in distributed environment.
    2. Controller Manager: Performs cluster-level functions, such as replicating components, keeping track of worker nodes, handling node failures
    3. Scheduler: Assigns a worker node to each deployable component of application.
    4. etcd: A distributed data store that stores the cluster configuration.
  • The components of the Control Plane control the state of the cluster, but they don’t run  applications/services, it is done by the (worker) nodes

  • Worker nodes are the machines that run your containerized applications. The task of running, monitoring, and providing services to applications is done by the worker nodes components. Worker nodes consist of following components:
    1. Container runtime: It runs container, most commonly used container runtime software are Docker or rkt.
    2. Kubelet: It talks to the API server and manages containers on its node.
    3. Kubernetes Service Proxy (kube-proxy): It load-balances network traffic between application components.

Kubernetes cluster Components

Multi-node Kubernetes cluster setup - Google Kubernetes Engine (GKE) cluster

In real world, Kubernetes clusters are multi-node cluster. Setting up a full-fledged, multi-node Kubernetes cluster isn’t a simple task, for demonstration and learning we will Google Kubernetes Engine and spin up multi-node cluster. Follow below steps to setup GCP account and setup multi-node cluster. GCP Reference

Kubernetes Engine, which is a hosted and managed deployment of Kubernetes that runs on Google Cloud Platform (using Compute Engine instances under the hood).

  1. If you do not have account setup in Google Cloud Platform(GCP), Go to Google console and setup an account. Please note in order to access Google Kubernetes Engine(GKE) -we have to provide CC details(Google will not charge immediately). Its Free for an year, if you have not used it go ahead, else create a new email and setup.
  2. Create a project, I have used name: gcpkubernetesdevinline. Project selector reference

  3. Add billing details to this project. Billing enable reference
  4. Launch Cloud Shell - Go to Google Cloud Console and from the upper-right corner of the console, click the Activate Cloud Shell button

  5.  Set default settings for the gcloud tool: Run below commands in Cloud Shell Terminal(opened in step 4).
    nikhilranjan234@cloudshell:~ (gcpkubernetesdevinline)$ gcloud config set compute/zone us-west1-a
    Updated property [compute/zone].
    API [compute.googleapis.com] not enabled on project [4118728221]. 
    Would you like to enable and retry (this will take a few minutes)? (y/N)? y Enabling service [compute.googleapis.com] on project [4118728221]... Operation "operations/acf.p2-4118728221-06e1ba2d-32c2-44b5-9b75-7784977588d0" finished successfully. nikhilranjan234@cloudshell:~ (gcpkubernetesdevinline)$ gcloud config set compute/region us-west1 Updated property [compute/region].

  6. Enable service: container.googleapis.com:
    nikhilranjan234@cloudshell:~ (gcpkubernetesdevinline)$ gcloud services enable container.googleapis.com
    Operation "operations/acf.p2-4118728221-f58bb66d-1c8f-4df2-b43e-22f6e1bafe07" finished successfully.

  7. Create clusters in GKE
    Create 3 node cluster and Verify number of nodes running. Use kubectl command now to list all the nodes in your cluster.
    nikhilranjan234@cloudshell:~ (gcpkubernetesdevinline)$ gcloud container clusters create gkekubedevinline --num-nodes 3
    Default change: VPC-native is the default mode during cluster creation for versions greater than 1.21.0-gke.1500. 
    To create advanced routes based clusters, please pass the `--no-enable-ip-alias` flag
    Note: Your Pod address range (`--cluster-ipv4-cidr`) can accommodate at most 1008 node(s).
    Creating cluster gkekubedevinline in us-west1-a...done.     
    Created [https://container.googleapis.com/v1/projects/gcpkubernetesdevinline/zones/us-west1-a/clusters/gkekubedevinline].
    kubeconfig entry generated for gkekubedevinline.
    NAME: gkekubedevinline
    LOCATION: us-west1-a
    MASTER_VERSION: 1.21.6-gke.1500
    MACHINE_TYPE: e2-medium
    NODE_VERSION: 1.21.6-gke.1500
    NUM_NODES: 3

    nikhilranjan234@cloudshell:~ (gcpkubernetesdevinline)$ kubectl get nodes NAME STATUS ROLES AGE VERSION gke-gkekubedevinline-default-pool-5f9f2c9a-850w Ready 5m39s v1.21.6-gke.1500 gke-gkekubedevinline-default-pool-5f9f2c9a-dr8b Ready 5m40s v1.21.6-gke.1500 gke-gkekubedevinline-default-pool-5f9f2c9a-vbrc Ready 5m40s v1.21.6-gke.1500
    Kubernetes cluster with 3 worker nodes
    • Each worker node runs Docker, the Kubelet and the kube-proxy
    • We(from outside K-cluster) will interact with the cluster through the kubectl command line client, which issues REST requests to the Kubernetes API server running on the master node.

  8. Deploy an application in cluster:
    We can use any container image to deploy in Kubernetes cluster. Here I am using nodejsapp container image which have created and publish in remote repository, refer Setup Docker, build docker image and push to Image registry
    nikhilranjan234@cloudshell:~ (gcpkubernetesdevinline)$ kubectl create deployment nodeapp-server --image=zytham/nodejsapp
    deployment.apps/nodeapp-server created

    Another way to deploy app in kubernetes cluster is to use the kubectl run command like: kubectl run nodeapp-server --image=zytham/nodejsapp --port=8080 --generator=run/v1

  9. Expose application as service:
    In order to access deployed nodejs application from web-browser/outside GCP environment, we have to expose this as service (having external static IP address).
    nikhilranjan234@cloudshell:~ (gcpkubernetesdevinline)$ kubectl expose deployment nodeapp-server --type LoadBalancer 
    --port 80 --target-port 8080
    service/nodeapp-server exposed

  10. Access pods and service details
    nikhilranjan234@cloudshell:~ (gcpkubernetesdevinline)$ kubectl get pods
    NAME                              READY   STATUS    RESTARTS   AGE
    nodeapp-server-569df4c455-dpjp6   1/1     Running   0          87s
    nikhilranjan234@cloudshell:~ (gcpkubernetesdevinline)$ kubectl get service nodeapp-server
    NAME             TYPE           CLUSTER-IP    EXTERNAL-IP     PORT(S)        AGE
    nodeapp-server   LoadBalancer   80:31823/TCP   108s
    nikhilranjan234@cloudshell:~ (gcpkubernetesdevinline)$ kubectl get services
    NAME             TYPE           CLUSTER-IP    EXTERNAL-IP     PORT(S)        AGE
    kubernetes       ClusterIP               443/TCP        19m
    nodeapp-server   LoadBalancer   80:31823/TCP   3m32s

  11. Access application:
    n0r0082@m-c02z31rnlvdt ~ % curl
    You've hit nodeapp-server-569df4c455-dpjp6

GKE Resource Cleanup 

To avoid incurring charges to your Google Cloud account for the resources used.

  1. Delete "nodeapp-server" service and "nodeapp-container" cluster from GKE environment.
    nikhilranjan234@cloudshell:~ (gcpkubernetesdevinline)$ kubectl delete service nodeapp-server
    service "nodeapp-server" deleted
    nikhilranjan234@cloudshell:~ (gcpkubernetesdevinline)$ gcloud container clusters delete nodeapp-container The following clusters will be deleted. - [nodeapp-container] in [us-west1-a]

  2. Go to application from Google console and click on Billing account and disable billing for project.

 Do not forget to remove billing otherwise you will charged and you will receive something like.. My trial has been expired.

Relationship between Kubernetes nodes, pods and containers 

  • Kubernetes pods are logical collection of co-related/co-located containers. Kubernetes does not allows accessing individual container but accessing pods are allowed.
    • Pods are atomic unit in Kubernetes. 
    • A pod is a group of one or more tightly related containers that will always run together on the same worker node and in the same Linux namespace(s). 
    • Each pod is like a separate logical machine with its own IP, hostname, processes, and so on, running a single application. 
    • All the containers in a pod will appear to be running on the same logical machine.
    • "kubectl get containers" is not valid command as Kubernetes does not allows accessing individual container.
  • Kubernetes worker nodes are physical or virtual machine which does run one or more containers in it.  
    Containers, pods, and physical worker nodes relationship

Benefits of using Kubernetes

  1. Simplifying application development:
    • Application runs in the same environment both during development and in production(application and its dependent resources are packaged as container image); it makes easier to sport any error locally. 
    • Kubernetes can automatically detect if the new version of application is in bad state and stop its rollout immediately.
  2. Simplifying application deployment:
    • Kubernetes exposes all its worker nodes as a single deployment platform, application developers can start deploying applications on their own and don’t need to know anything about the servers that make up the cluster.
  3. Better hardware utilization:
    • The ability to move applications around the cluster at any time allows Kubernetes to utilize the infrastructure much better than what you can achieve manually.
    • When we tell Kubernetes to run any application, we are letting it choose the most appropriate node to run the application on based on the description of the application’s resource requirements and the available resources on each node.
  4. Health checking and self-healing:
    • Kubernetes monitors your app components and the nodes they run on and automatically reschedules them to other nodes in the event of a node failure.
  5. Automatic scaling
    • Kubernetes can even automatically scale the whole cluster size up or down based on the needs of the deployed applications.

Reference: Kubernetes in Action By Marko Lukša


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