And by the way, using this API server service, you could actually manage an entire Kubernetes cluster.
How is it done?
It is done by using cube steel or cube control.
And Kub Control is a separate command line tool which allows you to connect to specific Kubernetes cluster
and manage it remotely.
And Cuba at Yale could be running even on your local computer.
And using such a little tool, you could manage a remote Kubernetes cluster.
And using such tool, you actually connect using rest API to API server service on the master node.
And such communication happens over https.
By the way, other nodes in the cluster, I mean worker nodes communicate with master node in the same
fashion.
It means that using such little tool you could manage any remote Kubernetes cluster.
That's it for Kubernetes Architecture Overview.
And now you know that Kubernetes cluster consists of the nodes and the one of the nodes is Master Node,
and it manages other nodes which are called worker nodes.
On each node there are ports and the ports are created automatically by Kubernetes.
And inside of the port there are containers, usually just a single container per port.
Also, please keep in mind that all containers inside of the port share namespaces of that port like
volumes or network IP address.
Also, ports are smallest units in Kubernetes, and the ports could be created that could be removed,
could be moved from one node to another.
This happens automatically without your intervention, but you have to design your application with
this in mind.
Both could be deleted on any moment of time.
Also there are different services which are running on different nodes, for example.
API server service is a central point of communication between master node and other worker nodes and
also using such API server service, you actually could manage actual Kubernetes cluster using Kupe
CTO tool, which has to be installed, for example, on your computer if you perform management from
your computer.
All right.
I don't want to dive deeper into the details of the Kubernetes, because this is very complicated tool,
and I want to focus more on practical tasks instead.
That's why now, after such overview, we will dive together with you into the practice and perform
different practical tasks together.
For example, we will create deployments, services, scale deployments, create custom Docker image
and create deployment based on that image and so on.