Google Cloud Kubernetes Engine Cluster

Clusters in GKE

 

Anatomy of a Kubernetes cluster

• The most simple way to think of Kubernetes is just like any other cluster.
• It's a collection of computers joined together to perform some function.
• A typical Kubernetes cluster will contain one or more masters and one or more nodes.
• Nodes are just communal gang variety computers.
• These can be large physical servers or even raspberry pies.

In the case of Google Kubernetes engine, they are virtual machines running in Google compute engine.

Kubernetes Master:

• Masters run several components that form what's called the control plane.
• This means they're in charge of controlling the cluster.
• They make decisions about the cluster.
• Such as where to schedule certain workloads.
• The master is responsible for the state of a cluster.
• It's constantly watching everything to make sure the state is as it should be.

Components of a Kubernetes Master.

• API Server:
• The API Server is the front end of the control plane it exposes the API for all the master functions.
• Every time you communicate with the master or anything else communicates with the master It would be through this API.
• Most of the time you'll use google cloud counsel or command line tool but in the background it's always talking to this API.
• Once a cluster is up and running your day to day interaction is just going to be with that API Server. 
• And with GKE there is a good reason you don't need to worry too much about this individual components.
• etcd
• etcd  is Kubernetes own database.
• Storing all of it's configuration in state.
• We call it a database but really etcd is just a key value store.
• It is very well known one that is designed for scale and higher availability.
• Scheduler
• The Scheduler is responsible for scheduling work loads.
• That means is when you want to deploy a container the scheduler will pick a node to run that container on.
• The node it picks can be affected by all kinds of factors such as the current load on each available node.
• The requirements of your container and some other customizable constraints.
• Cloud Controller Manager
• The Cloud Controller Manager, is what allows Kubernetes to work with cloud platforms.
• Kubernetes itself is an open source project  with contributions from lots of large companies
• not just Google So it doesn't natively contain functionality for google cloud only. 
• This manager is responsible for handling things like networking and load balancing as they translate to the product and services of a particular cloud platform.
• Kube Controller Manager
• Its job is to manage a handful of controllers in the cluster.
• The controllers themselves look after things like nodes and a few other objects.

Kubernetes Node

• Nodes run components that form the runtime environment.
• There basically the workers with a container runtime.
• In this node computers, provide the resources of the cluster.
• All of the CPU and RAM can be used to run containers
• When you deploy a container in Kubernetes the master will pick a node to run it on. 
• These are going to be our actual virtual machines that will run containers for us. 
• They're a lot more straightforward than the master.

Component's of Kubernetes node  

• Kubelet:
• It is an agent for Kubernetes.
• It communicates with the control play and takes instructions such as deploying containers when it's told to.
• Kube-proxy:
• It is responsible for managing network connections in and out of the node.
• Actual Container Runtime:
• Just like when we run our first container in cloud shell the noble run docker as a container runtime to allow it to run containers.

How to build a Kubernetes cluster?

• The hard way.
• You'll need provision of virtual machines for you master and your nodes.
• You'll need to install the Kubernetes software create a network overlay.
• Set up certificates so that all of the components can talk to each other secularly.
• The easy way.
• Use GKE.
• GKE provisions and manages the underlying cloud resources automatically.

GKE is a fully managed service

• It will create masters and nodes for you to your specification using a container-optimized operating system.
• You design your cluster within GKE without having to build or maintain individual masters or nodes.
• It comes with built-in automatic upgrading, automatic self-repair.
• It has many options for fine grain resource control and cluster scaling.
• Its integrated with all of the other products and services Google cloud platform.
• You don't even touch the master control plane.
• It is completely managed for you.
• It's made of compute engine VMs just like your nodes, but they won't even show up in your project.
• Google's own CRET are looking after them for you.
• Abstracting away the control plane takes away a lot of the operation overhead.

How do we operate and interact with GKE

• Google Cloud Console.
• Kubernetes functionality is exposed to us to the simple UI of the cloud console.
• Command lines for Kubernetis
• Kubectl for operating a running cluster
• Kubectl allows us to interact with Kubernetes by defining the objects we want to deploy.
• These objects are just abstractions of what we want to run and how we want to run it.
• Kubectl takes our instructions and passes them to the API server.
• Communicate with API Server
• Perform their own function to carry out our commands.
• Create and manage life-cycle of Kubernetes objects
• Everything in Kubernetes is an object and every object has a state.