Fast-Kubernetes
This repo covers Kubernetes objects' and components' details (Kubectl, Pod, Deployment, Service, ConfigMap, Volume, PV, PVC, Daemonset, Secret, Affinity, Taint-Toleration, Helm, etc.) fastly, and possible example usage scenarios (HowTo: Hands-on LAB) in a nutshell. Possible usage scenarios are aimed to update over time.
Prerequisite
- Have a knowledge of Container Technology (Docker). You can learn it from here => Fast-Docker
Keywords: Containerization, Kubernetes, Kubectl, Pod, Deployment, Service, ConfigMap, ReplicaSet, Volume, Cheatsheet.
Note: K8s objects and objects feature can be updated/changed in time. While creating this repo, the version of K8s was v1.22.3. Some sections are trying to be kept up to date. Especially Creating K8s Cluster with Kubeadm and Containerd.
Quick Look (HowTo): Scenarios - Hands-on LAB
- LAB: K8s Creating Pod - Imperative Way
- LAB: K8s Creating Pod - Declarative Way (With File) - Environment Variable
- LAB: K8s Multicontainer - Sidecar - Emptydir Volume - Port-Forwarding
- LAB: K8s Deployment - Scale Up/Down - Bash Connection - Port Forwarding
- LAB: K8s Rollout - Rollback
- LAB: K8s Service Implementations (ClusterIp, NodePort and LoadBalancer)
- LAB: K8s Liveness Probe
- LAB: K8s Secret (Declarative and Imperative Way)
- LAB: K8s Config Map
- LAB: K8s Node Affinity
- LAB: K8s Taint-Toleration
- LAB: K8s Daemonset - Creating 3 nodes on Minikube
- LAB: K8s Persistent Volume and Persistent Volume Claim
- LAB: K8s Stateful Sets - Nginx
- LAB: K8s Job
- LAB: K8s Cron Job
- LAB: K8s Ingress
- LAB: Helm Install & Usage
- LAB: K8s Cluster Setup with Kubeadm and Containerd
- LAB: K8s Cluster Setup with Kubeadm and Docker
- LAB: Helm-Jenkins on running K8s Cluster (2 Node Multipass VM)
- LAB: Enable Dashboard on Real K8s Cluster
- LAB: K8s Monitoring - Prometheus and Grafana
- Kubectl Commands Cheatsheet
- Helm Commands Cheatsheet
Table of Contents
- Motivation
- What is Kubernetes?
- Kubernetes Architecture
- Kubernetes Components
- Installation
- Kubectl Config – Usage
- Pod: Creating, Yaml, LifeCycle
- MultiContainer Pod, Init Container
- Label and Selector, Annotation, Namespace
- Deployment
- Replicaset
- Rollout and Rollback
- Network, Service
- Liveness and Readiness Probe
- Resource Limit, Environment Variable
- Volume
- Secret
- ConfigMap
- Node – Pod Affinity
- Taint and Toleration
- Deamon Set
- Persistent Volume and Persistent Volume Claim
- Storage Class
- Stateful Set
- Job, CronJob
- Authentication, Role Based Access Control, Service Account
- Ingress
- Dashboard
- Play With Kubernetes
- Helm: Kuberbetes Package Manager
- Kubernetes Commands Cheatsheet
- Helm Commands Cheatsheet
- Kubernetes Cluster Setup: Kubeadm, Containerd, Multipass
- Monitoring Kubernetes Cluster with SSH, Prometheus and Grafana
- Other Useful Resources Related Kubernetes
- References
Motivation
Why should we use Kubernetes? "Kubernetes is a portable, extensible, open-source platform for managing containerized workloads and services, that facilitates both declarative configuration and automation. It has a large, rapidly growing ecosystem. Kubernetes services, support, and tools are widely available." (Ref: Kubernetes.io)
What is Containerization? What is Container Orchestration?
- "Containerization is an operating system-level virtualization or application-level virtualization over multiple network resources so that software applications can run in isolated user spaces called containers in any cloud or non-cloud environment" (wikipedia)
- With Docker Environment, we can create containers.
- Kubernetes and Docker Swarm are the container orchestration and management tools that automate and schedule the deployment, management, scaling, and networking of containers.
Features
- Service discovery and load balancing: Kubernetes can expose a container using the DNS name or using their own IP address. If traffic to a container is high, Kubernetes is able to load balance and distribute the network traffic so that the deployment is stable.
- Storage orchestration: Kubernetes allows you to automatically mount a storage system of your choice, such as local storages, public cloud providers, and more.
- Automated rollouts and rollbacks: You can describe the desired state for your deployed containers using Kubernetes, and it can change the actual state to the desired state at a controlled rate.
- Automatic bin packing: You tell Kubernetes how much CPU and memory (RAM) each container needs. Kubernetes can fit containers onto your nodes to make the best use of your resources.
- Self-monitoring: Kubernetes checks constantly the health of nodes and containers
- Self-healing: Kubernetes restarts containers that fail, replaces containers, kills containers that don't respond to your user-defined health check
- Automates various manual processes: for instance, Kubernetes will control for you which server will host the container, how it will be launched etc.
- Interacts with several groups of containers: Kubernetes is able to manage more cluster at the same time
- Provides additional services: as well as the management of containers, Kubernetes offers security, networking and storage services
- Horizontal scaling: Kubernetes allows you scaling resources not only vertically but also horizontally, easily and quickly
- Container balancing: Kubernetes always knows where to place containers, by calculating the “best location” for them
- Run everywhere: Kubernetes is an open source tool and gives you the freedom to take advantage of on-premises, hybrid, or public cloud infrastructure, letting you move workloads to anywhere you want
- Secret and configuration management: Kubernetes lets you store and manage sensitive information
What is Kubernetes?
- "Kubernetes is a portable, extensible, open-source platform for managing containerized workloads and services, that facilitates both declarative configuration and automation. It has a large, rapidly growing ecosystem. Kubernetes services, support, and tools are widely available." (Ref: Kubernetes.io)
(Ref: Kubernetes.io)
Kubernetes Architecture
Kubernetes Components (Ref: Kubernetes.io)
- Control Plane: User enters commands and configuration files from control plane. It controls all cluster.
- API Server: "It exposes the Kubernetes API. The API server is the front end for the Kubernetes control plane."
- Etcd: "Consistent and highly-available key value store used as Kubernetes' backing store for all cluster data (meta data, objects, etc.)."
- Scheduler: "It watches for newly created Pods with no assigned node, and selects a node for them to run on.
- Factors taken into account for scheduling decisions include:
- individual and collective resource requirements,
- hardware/software/policy constraints,
- affinity and anti-affinity specifications,
- data locality,
- inter-workload interference,
- deadlines."
- Factors taken into account for scheduling decisions include:
- Controller Manager: "It runs controller processes.
- Logically, each controller is a separate process, but to reduce complexity, they are all compiled into a single binary and run in a single process.
- Some types of these controllers are:
- Node controller: Responsible for noticing and responding when nodes go down.
- Job controller: Watches for Job objects that represent one-off tasks, then creates Pods to run those tasks to completion.
- Endpoints controller: Populates the Endpoints object (that is, joins Services & Pods).
- Service Account & Token controllers: Create default accounts and API access tokens for new namespaces"
- Cloud Controller Manager: "It embeds cloud-specific control logic. The cloud controller manager lets you link your cluster into your cloud provider's API, and separates out the components that interact with that cloud platform from components that only interact with your cluster. The cloud-controller-manager only runs controllers that are specific to your cloud provider
- The following controllers can have cloud provider dependencies:
- Node controller: For checking the cloud provider to determine if a node has been deleted in the cloud after it stops responding
- Route controller: For setting up routes in the underlying cloud infrastructure
- Service controller: For creating, updating and deleting cloud provider load balancers."
- The following controllers can have cloud provider dependencies:
- Node: "Node components run on every node, maintaining running pods and providing the Kubernetes runtime environment."
- Kubelet: "An agent that runs on each node in the cluster. It makes sure that containers are running in a Pod. The kubelet takes a set of PodSpecs that are provided through various mechanisms and ensures that the containers described in those PodSpecs are running and healthy."
- Kube-proxy: "It is a network proxy that runs on each node in your cluster, implementing part of the Kubernetes Service concept.
- It maintains network rules on nodes. These network rules allow network communication to your Pods from network sessions inside or outside of your cluster.
- It uses the operating system packet filtering layer if there is one and it's available. Otherwise, kube-proxy forwards the traffic itself."
- Container Runtime: "The container runtime is the software that is responsible for running containers.
- Kubernetes supports several container runtimes: Docker, containerd, CRI-O, and any implementation of the Kubernetes CRI (Container Runtime Interface)"
Installation
Download:
- Kubectl: The Kubernetes command-line tool, kubectl, allows you to run commands against Kubernetes clusters.
- Minikube: It is a tool that lets you run Kubernetes locally. It runs a single-node Kubernetes cluster on your personal computer (https://minikube.sigs.k8s.io/docs/start/)
- KubeAdm: You can use the kubeadm tool to create and manage Kubernetes clusters. This is for creating cluster with computers (Goto: LAB: K8s Kubeadm Cluster Setup).
from here=> https://kubernetes.io/docs/tasks/tools/
For learning K8s and running on a computer, Kubectl and Minikube are enough to install.
PS: Cloud providers (Azure, Google Cloud, AWS) offer managed K8s (control plane is managed by cloud provides). You can easily create your cluster (number of computer and details) and make connection with Kubectl (using CLI get-credentials of cluster on the cloud)
Kubectl Config – Usage
Config File
- You can communicate with K8s cluster in different ways: REST API, Command Line Tool (CLI-Kubectl), GUI (kube-dashboard, etc.)
- After installation, you can find the kubernetes config file (C:\Users\User.kube\config) that is YAML file.
- Config file contains 3 main parts: Clusters (cluster certificate data, server, name), Context (cluster and user, namespace), Users (name, config features, certificates, etc.)
Usage
- Kubectl is our main command line tool that connects minikube. There are many combination of commands. So it is not possible to list all commands.
- When run "kubectl" on the terminal, it can be seen some simple commands. Also "kubectl
--help" gives more information. - Pattern: kubectl [get|delete|edit|apply] [pods|deployment|services] [podName|serviceName|deploymentName]
- Example: "kubectl get pods podName", "kubectl delete pods test_pod", "kubectl describe pods firstpod", etc.
- All necessary/most usable commands are listed in the "Kubernetes Commands Cheatsheet". Please have a look to get more information and usage.
Pod: Creating, Yaml, LifeCycle
- Pod is the smallest unit that is created and managed in K8s.
- Pods may contain more than 1 container, but mostly pods contain only 1 container.
- Each pod has unique id (uid).
- Each pod has unique IP address.
- Containers in the same Pod run on the same Node (computer), and these containers can communicate with each other on the localhost.
- Creation of the first pod, IMPERATIVE WAY (with command):
- Please have a look Scenario (Creating Pod - Imperative way, below link) to learn more information about the pod's kubectl commands.
- how to create basic K8s pod using imperative commands,
- how to get more information about pod (to solve troubleshooting),
- how to run commands in pod,
- how to delete pod.
Goto the Scenario: [LAB: K8s Creating Pod - Imperative