Container Orchestration with Kubernetes

Study Notes

Containers are needed to solve several challenges, such as compatibility and dependency problems, long setup times, and different Dev/Test/Prod environments.
A container consists of an entire runtime environment: an application, its dependencies, libraries, and other binaries, and configuration files needed to run it, bundled into one package.

Containers run on top of the host OS kernel, whereas Virtual Machines run their own OS kernel.
Containers share the host OS kernel, whereas Virtual Machines have their own OS kernel.

Docker is a container runtime that allows you to package, ship, and run applications in containers.
Docker consists of:
- Docker daemon (dockerd) that listens for Docker API requests and manages Docker objects.
- Docker client (docker) that sends commands to dockerd.
- Docker registry that stores Docker images.
- Docker Hub, a public registry that anyone can use.

Containers orchestration is necessary to manage the lifecycle of containers, especially in large, dynamic environments.
Orchestration automates the scheduling, deployment, networking, scaling, health monitoring, and management of containers.
A use case for containers orchestration is when you have multiple applications running on a single server and need to scale, deploy, and manage them.

Managing a small number of containers on a few hosts using Docker CLI is adequate, but falls short of automating complex deployments on multiple hosts.

Kubernetes is an open-source container orchestration engine for automating deployment, scaling, and management of containerized applications.
Kubernetes architecture consists of:
- Node: a virtual or physical machine that runs containers.
- Cluster: a set of nodes that run containerized applications.
- Master Node: a node that controls and manages a set of worker nodes.
- API Server: validates and configures data for API objects.
- etcd: a consistent and highly-available key-value store used as Kubernetes' backing store.
- Kubelet: an agent that runs on each node and ensures containers are running in a pod.
- Container Runtime: software that runs containers, such as Docker, containerd, or CRI-O.
- Controller: control loops that watch the state of the cluster and make changes where needed.
- Scheduler: selects a node for newly created pods to run on.