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Introduction to Kubernetes🔗

Kubernetes Overview🔗

What is Kubernetes (k8s) ?🔗

  • Open-sourcer container orchestration tool designed to automate, deploying, scaling & operating containerized applications
  • Born out of Google’s experience running production workloads at scale
  • Allows orgs to increase their velocity by releasing and recovering faster
  • It is a distributed systems with multiple machines (Machines may be physical, virtual, on-prem or in cloud)
  • schedules containers on machine
  • moves containers as machines are added/removed
  • can use different container runtimes
  • modular, extensible design

Main Advantage : Declarative Configuration, Deploy Containers, Wire up networking, scale and expose services

Feature Hightlights🔗

  • Automated Deployment rollout and rollback
  • Seamless horizontal scaling
  • Secret Management
  • Service Discovery and load balancing
  • Linux and Windows container support
  • Simple log collection
  • Stateful application support
  • Persistent Volume Management
  • CPU and memory quotas
  • Batch job processing
  • Role-based access control (RBAC)

Competitors of k8s🔗

DC/OS🔗

  • Distributed Cloud Operating System
  • Pools Compute Resources into a uniform task pool
  • Supports many different types of workloads
  • Attractive to organization not only using containers
  • includes package manager to easily deploy popular systems
  • Can even run Kubernetes on DC/OS

ECS (Elastic Container Service)🔗

  • aws’s first entry in container orchestration
  • create pools of compute resources
  • API calls to orchestrate containers
  • EC2 compute instances managed by you or by AWS (Fargate)
  • Only available in AWS

Docker Swarm🔗

  • Official docker solution for orchestrating containers across a cluster of machines
  • builds a cluster from multiple docker hosts
  • works natively with the docker command
  • used by Docker’s enterprise edition
  • docker also provides full support of Kubernetes to easily switch

Deploying Kubernetes🔗

Single-Node Kubernetes Clusters🔗

Tools

  • docker on Mac/windows already includes kubernetes
  • minicube
  • kubeadm (NOTE : create on host not a vm)

Create ephemeral clusters that start quickly and are in pristine state for testing application in Kubernetes.

Kubernetes-in-Docker (kind) is made for this use case.

Multi-Node Kubernetes Cluster🔗

  • for production workloads
  • horizontal scaling
  • tolerate node failures

Which solution is best ? Ask several key question

  • Control vs Effort to Maintain
  • fully-managed solution free you from routine maintenance
    • often lag the latest k8s release
    • Examples : EKS, AKS (Azure), GKE (GCP)
    • Full Control Examples : kubespray, kops, kubeadm
  • Do you already have expertise with a particular cloud provider
  • Do you need enterprise support ?
    • several vendors offer enterprise support and additional features on top of k8s
    • Openshift by RedHat, Pivotal Container Service(PKS) and Rancher
  • Are you concerned about vendor lock-in ?
    • use open source solution : kubespray or rancher
  • on-prem, in cloud or both ?
    • All EKS, AKS, GKE allows on-prem servers
  • Linux, windows or both containers ?
    • ensure similar nodes are in your cluster as per requirement

Kubernetes Architecture🔗

  • kubernetest introduces its own dialect to orchestration space
  • Cluster refers to all of the machines collectively and can be thought of as the entire running system
  • Nodes are the machines in the cluster
  • Nodes are categorized as worker or masters
  • Worker Node includes software to run containers managed by the Kubernetes control plane
  • Master nodes run the control plane
  • The Control Plane is a set of APIs and software that Kubernetes users interact with
  • The APIs and Software are referred to as Master Components

Scheduling🔗

  • Control Plane Schedules containers onto nodes
  • Scheduling decision considers required CPU and other factors
  • scheduling here refers to the decisions process of placing containers onto node

Kubernetes Pods🔗

  • Group of containers
  • Pods are smallest building block in k8s
  • more complex abstraction are build on pods

Service🔗

  • Services define networking rules for exposing groups of pods
    • to other pods
    • to public internet

Kubernetes Deployments🔗

  • Mange deployign configs changes to running pods
  • horizontal scaling

Resource for Further Reading (Advanced)

The Kubernetes API Server🔗

  • modify cluster state information by sending request to the k8s api server
  • API Server is a master component that acts as frontend for the cluster

Interacting with Kubernets

  1. Rest API
    • It is possible but not common to work directly with API server
    • only if there is not client library for your programming language
  2. Client Library
    • handles auth and managing individual REST API request and responses
    • kubernetes maintains official client libraries in python, go, java, .NET, javascript, etc along with community maintained libraries.
  3. kubectl : Kube Control
    • Issues high-level command that are translated in REST API Call
    • works with local/remote clients
    • can manage different types of k8s resoruces and provides debugging and introspection

Example Kubectl Commands🔗

  • kubectl create (resources : pods, service, etc)
  • kubectl delete
  • kubectl get : gets list of resources of a given type. kubectl get pods or kubectl get all
  • kubectl descibe <resource> [resource_name] : describe to print detailed info about a resource(s)
  • kubectl logs to print container logs
  1. Web Dashboard to interact with Kubernetes API