What Are Kubernetes Containers?

Kubernetes is an open-source container orchestration platform originally developed by Google. Container orchestration refers to the automation of deployment, scaling, and management of containerized applications across various environments—whether physical servers, virtual machines, or hybrid cloud setups. It simplifies complex tasks like scaling, networking, and failover for containers, ensuring applications run consistently and efficiently.

The name Kubernetes originates from the Greek word for “helmsman” or “pilot.” Within Google, the internal project was known as Project Seven (Borg) before its public release in 2014. After running production workloads at scale for over a decade, Google open-sourced Kubernetes, and it is now maintained by the Cloud Native Computing Foundation (CNCF).

What Is Kubernetes?
Kubernetes (K8s) is an open-source platform designed to automate the deployment, scaling, and management of containerized applications. It orchestrates containers across clusters of machines to ensure high availability, optimal resource utilization, and resilience.

Today, Kubernetes has become the foundation of modern cloud-native architectures, simplifying the management of distributed microservices applications across diverse infrastructures.

What Are Kubernetes Containers?
Kubernetes itself doesn’t run applications directly—it orchestrates containers, which are lightweight, portable units that package an application and all its dependencies. Kubernetes ensures these containers are deployed efficiently, scaled automatically based on traffic, and maintained through self-healing mechanisms.

Core functions of Kubernetes containers include:

Load Balancing

Service Discovery

Self-Healing

Horizontal Scaling

These capabilities make Kubernetes ideal for running containerized workloads in production.

Containers and Kubernetes: How They Work Together
Containers are lightweight, standalone software packages that include everything needed to run an application—code, runtime, libraries, and dependencies. They ensure consistency across environments, from a developer’s laptop to production servers.

Kubernetes manages these containers across a cluster of machines, handling tasks like scheduling, scaling, failover, and networking. Together, they enable seamless application deployment, scaling, and lifecycle management in cloud-native environments.

Containerization Using Kubernetes
Containerization with Kubernetes refers to deploying applications—whether microservices or monoliths—using the Kubernetes orchestration engine. Kubernetes provides advanced features such as load balancing, self-healing, rolling updates, and auto-scaling, making it a powerful tool for production environments.

To deploy a containerized application in Kubernetes:

Build a container image using Docker. This image includes the application and all necessary dependencies.

Push the image to a container registry (e.g., Docker Hub, Amazon ECR, or Google Container Registry).

Create a manifest file (YAML format) defining how Kubernetes should deploy the application (Deployment, DaemonSet, etc.).

Example Deployment Manifest:

apiVersion: apps/v1
kind: Deployment
metadata:
name: my-deployment
spec:
replicas: 3
selector:
matchLabels:
app: my-app
template:
metadata:
labels:
app: my-app
spec:
containers:
- name: my-app
image: my-app:latest
Deploy the application with:

kubectl apply -f deployment.yaml
Kubernetes then creates the required resources (Pods, Services, and ReplicaSets) to run the application.

Understanding Container Technology
Containerization is a form of OS-level virtualization that allows multiple isolated applications to run on the same kernel. Unlike virtual machines that virtualize hardware, containers share the host OS kernel, resulting in faster startup times and better resource utilization.

Aspect Virtual Machines (VMs) Containers
Virtualization Type Hardware-level OS-level
Boot Time Minutes Seconds
Resource Allocation Pre-allocated Dynamic
Isolation Complete (separate OS) Process-level
Efficiency Lower (due to hypervisor overhead) Higher
Because containers are lightweight and portable, they can run on bare metal, VMs, on-premises servers, or in any public cloud environment.

What Is Docker?
Docker is a popular containerization platform that enables developers to build, package, and distribute applications as portable container images. Each Docker image contains the code, dependencies, and runtime required to execute an application consistently across environments.

Docker simplifies:

Application packaging

Continuous integration and delivery (CI/CD)

Rapid scaling and deployment

Container images are stored in container registries like:

Docker Hub

Amazon ECR (Elastic Container Registry)

Google Container Registry (GCR)

Container Runtimes
A container runtime is responsible for running and managing the lifecycle of containers on a host. It handles tasks such as starting, stopping, and maintaining containers.

Common container runtimes include:

Docker

containerd

CRI-O

Podman

Kubernetes supports multiple runtimes through the Container Runtime Interface (CRI), enabling flexibility and compatibility across environments.

Kubernetes Pods
A Pod is the smallest deployable unit in Kubernetes. It encapsulates one or more containers that share the same storage, network, and runtime context. Pods are ephemeral, meaning they are automatically replaced by Kubernetes if they fail.

Pods can host:

A single container (most common)

Multiple tightly coupled containers (sidecar pattern)

Pods can also mount persistent storage volumes to retain data across restarts.

Kubernetes Architecture
Kubernetes architecture is composed of a control plane (master node) and worker nodes.

Control Plane Components
kube-apiserver: Acts as the main entry point to the cluster, managing all API requests.

etcd: A distributed key-value store holding cluster state and configuration.

kube-scheduler: Assigns Pods to nodes based on resource availability and policies.

kube-controller-manager: Ensures the cluster state matches the desired configuration.

cloud-controller-manager: Integrates Kubernetes with external cloud services.

Worker Node Components
kubelet: Ensures containers in Pods are running as defined.

kube-proxy: Manages network communication between services and Pods.

container runtime: Runs and manages containers on each node.

network agent: Implements the software-defined networking layer.

Types of Containers Supported by Kubernetes
Kubernetes supports several container runtimes:

Docker: Most popular and historically the default runtime.

Podman: Docker-compatible runtime supporting rootless containers.

CRI-O: Kubernetes-optimized runtime used in Red Hat OpenShift.

containerd: Lightweight runtime used by default in many modern Kubernetes distributions.

Others: LXC and rkt (less common today).

Installing Kubernetes on Linux (Step-by-Step)
Step 1: Update the package manager

sudo apt-get update
Step 2: Install transport utilities

sudo apt-get install -y apt-transport-https
Step 3: Install Docker

sudo apt install docker.io
sudo systemctl start docker
sudo systemctl enable docker
Step 4: Install prerequisites

sudo apt-get install curl
Step 5: Add Kubernetes GPG key and repository

sudo curl -s https://packages.cloud.google.com/apt/doc/apt-key.gpg | sudo apt-key add -
echo "deb https://apt.kubernetes.io/ kubernetes-xenial main" | sudo tee /etc/apt/sources.list.d/kubernetes.list
sudo apt-get update
Step 6: Install Kubernetes components

sudo apt-get install -y kubelet kubeadm kubectl
Step 7: Initialize the master node

sudo swapoff -a
sudo kubeadm init
Step 8: Configure kubectl access

mkdir -p $HOME/.kube
sudo cp -i /etc/kubernetes/admin.conf $HOME/.kube/config
sudo chown $(id -u):$(id -g) $HOME/.kube/config
Step 9: Deploy a network plugin (Flannel)

kubectl apply -f https://raw.githubusercontent.com/coreos/flannel/master/Documentation/kube-flannel.yml
Step 10: Verify installation

kubectl get pods --all-namespaces
Docker vs Kubernetes
Aspect Docker Kubernetes
Definition Containerization tool for building and running containers Orchestration platform for managing containerized applications
Deployment Managed via Docker CLI or Docker Compose Managed via kubectl and YAML manifests
Scaling Manual Automated (Horizontal Pod Autoscaler)
Networking Limited to host or bridge networks Advanced networking with service discovery and load balancing
Purpose Create and manage containers Manage clusters of containers at scale
Ingress vs Kubernetes Services
Aspect Kubernetes Ingress Kubernetes Service
Definition Manages external access to services Exposes Pods as a network service
Purpose Provides HTTP/HTTPS routing Facilitates internal/external connectivity
Load Balancing Layer 7 (Application) Layer 4 (Network)
Configuration Requires Ingress Controller Defined using Service resources
Routing Supports advanced URL/host-based routing Basic routing for internal communication
Features of Kubernetes Containers
Multi-host scheduling using kube-scheduler

Automatic scaling and failover

Extensible architecture with plugins and add-ons

Service discovery through DNS and environment variables

Persistent storage with Persistent Volumes

Versioned APIs for backward compatibility

Built-in monitoring with cAdvisor, Prometheus, and Metrics Server

Secrets management for sensitive data

Advantages of Kubernetes Containers
Scalability: Easily increase or decrease replicas based on demand

High Availability: Self-healing and automatic failover mechanisms

Portability: Platform-agnostic—runs anywhere

Automation: Handles rolling updates, deployments, and scaling automatically

Flexibility: Supports blue-green, canary, and A/B deployments

Challenges and Limitations
Despite its power, Kubernetes introduces certain complexities:

Steep learning curve

Complex networking setup

Higher resource consumption

Limited native Windows container support

Conclusion
Kubernetes containers revolutionize how modern applications are developed, deployed, and managed. By combining Docker’s containerization with Kubernetes’ orchestration, organizations gain scalability, reliability, and agility in their infrastructure—making Kubernetes the de facto standard for cloud-native computing.