Udemy: Kubernetes for Beginners
Open source project built by Google
Containers are necessary because they isolate compatibility between various components and the underlying infrastructure
Containers make setting up dev/test environments very easy
All somebody would have to do is make sure docker is installed on the system
They can have their own processes, network, mounts, etc, but they all share the same OS Kernel
All OS's consist of two things:
OS Kernel: Total control over interacting with hardware
Software: It makes the OS different (MacOS, Ubunut Linux, etc)
Docker utilizes underlying kernel
You can't run a windows container on a server that runs linux, instead you would need a windows VM
Containers vs VMs
VMs have the OS on the actual hardware itself whereas docker runs separate of the OS
VMs require much more disk space and use more CPU
Docker containers can boot up in a matter of seconds
In a VM, you can have both linux and windows on the same hypervisor
Docker Basics
Docker Registry: You can find images of most common DBs, OSs, etc with simple commands
Ex. docker run mongodb
Containers are running instances of images that are insulated
Developers can now create a docker file, which creates an image, and that image can be ran on a container platform
This makes it easy for operations teams to set up and run an application
Container Orchestration
How do you run a container in production that requires other resources and or has variable load?
You need an underlying platform to orchestrate the activity between containers and automatically scale up/down
Ex. Kubernetes, Docker Swarm, MESOS, etc
Tools like K8s make appications highly available & load balanced with a set of simple config files
K8s Architecture
Nodes:
machine (physical or virtual) in which K8s is installed
worker machine where containers will be launched by k8s
AKA "minions" in the past
Cluster:
set of nodes grouped together
helps load balance
Master:
Responsible for moving workload from a failed node to another node
The master is a node itself that watches and orchestrates containers on other nodes
When installing K8s on a server, you are actually installing these services:
API Server
frontend for K8s
etcd
distributed key value store to store data used to manage the cluster
manages locks between masters
kubelet
agent is responsible for the containers on the node it is running are working as expected
container runtime
underlying software to run containers
i.e. docker
controller
brain behind orchestration
noticing and responding when things fail
may bring up new containers in such cases
scheduler
responsible for distributing work or containers across multiple nodes
Master vs Worker Nodes
The worker node is where the containers are hosted and that usually has docker installed or something equivalent
The master server has the kube-apiserver while the worker nodes have kubelet agent
The master holds the etcd keystore, controller, and scheduler
kubectl is a CLI tool that is used to deploy and manage apps on a K8s cluster
Kubernetes Pods
K8s does not deploy containers directly on the worker nodes
A pod is a single instance of an application and is the smallest object you can create in K*s
Simple example:
single node K8s cluster with a single instance in a single container encapsulated in a pod
If you need to scale, you need to add additional instances of your app
to do this, you create a brand new pod on the same node
You can always deploy additional pods on a new node in the cluster to expand the overall resources
never add additional containers to an existing pod
Multi-container PODs
a single pod can have multiple containers, but typically the containers are not of the same kind
you may have a "helper" pod that lives along side your application container
They can refer to each other as localhost and can also share the same storage space
You deploy your container by running docker run command and you keep running that to create new containers
If you also have helper containers, it is best to define those in separate pods so that they scale together
Even if your app has a single container, K8s requires you to use PODs
Installing MiniKube locally
Requirements:
1) kubectl
2) virtualbox (or some other virtualization driver like hyper-v, which may already be installed)
3) minikube
YAML
spacing in YAML is very important
arrays are defined with a "-"
Dictionary vs List vs List of Dictionaries
Dictionary is unordered while a list/array is ordered
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