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Kubernetes

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In brief · quick answer

Kubernetes (K8s) is an open source platform for automating deployment, scaling, and management of containerized applications. It turns a cluster of servers into a single pool of compute resources.

§ 1 Definition

Kubernetes (often shortened to K8s) is Google's open source container orchestration system, now maintained by the Cloud Native Computing Foundation. It manages clusters of machines as a unified computing platform. You tell Kubernetes what you want running (which containers, how many replicas, what resources they need), and Kubernetes handles scheduling, scaling, networking, and self-healing. If a container crashes, Kubernetes restarts it. If traffic spikes, Kubernetes scales up. If a node fails, Kubernetes redistributes the workload. It has become the standard for running production containerized applications at scale.

§ 2 Why Kubernetes Exists

Running containers manually with Docker is fine for a few services on a single server. Once you have dozens of services across multiple servers, you need orchestration. Kubernetes automates the placement of containers onto nodes, load balancing between them, rolling out updates without downtime, scaling based on CPU/memory or custom metrics, storing secrets and configuration, and connecting services regardless of which node they run on. It is the operating system for the data center.

§ 3 Key Concepts

A Cluster is a set of machines (nodes) running Kubernetes. Pods are the smallest deployable unit: one or more containers that share networking and storage. Deployments manage stateless applications with desired replica counts and rolling updates. Services provide stable networking to a set of pods. Ingress exposes HTTP/HTTPS routes from outside the cluster. ConfigMaps and Secrets manage configuration and sensitive data separately from containers.

§ 4 When You Need Kubernetes

Kubernetes is powerful but complex. You need it when you have multiple microservices that need to scale independently, when you need zero-downtime deployments, or when your application spans multiple servers. For a single application on a single server, Docker alone is sufficient. Kubernetes introduces significant operational overhead; managed Kubernetes services (EKS, GKE, AKS) reduce but don't eliminate it.

§ 5 Note

Managed Kubernetes (Amazon EKS, Google GKE, Azure AKS) is the recommended way to run K8s unless you have a dedicated infrastructure team. Self-managed clusters are significantly more work.

§ 6 In code

```yaml
# Kubernetes Deployment manifest
apiVersion: apps/v1
kind: Deployment
metadata:
  name: web-app
spec:
  replicas: 3
  selector:
    matchLabels:
      app: web-app
  template:
    metadata:
      labels:
        app: web-app
    spec:
      containers:
      - name: app
        image: my-app:latest
        ports:
        - containerPort: 3000
        resources:
          requests:
            cpu: 250m
            memory: 256Mi
          limits:
            cpu: 500m
            memory: 512Mi
```

§ 7 Common questions

Q. Is Kubernetes the same as Docker?: A. No. Docker creates and runs containers. Kubernetes orchestrates containers across multiple machines. They work together: Docker packages the containers, Kubernetes manages them.
Q. Is Kubernetes overkill for a small project?: A. Almost certainly. For small projects, use Docker Compose or a platform like Vercel or Netlify. Kubernetes overhead only pays off at scale.

Key takeaways

Kubernetes orchestrates containers across a cluster of machines, automating deployment, scaling, and healing.
It handles container placement, load balancing, rolling updates, and self-healing automatically.
Powerful but complex. Use managed K8s services (EKS, GKE, AKS) unless you have dedicated ops resources.
Overkill for small projects. Start with Docker Compose or PaaS platforms.

How Atomic Glue helps

We design and manage Kubernetes clusters for clients who need container orchestration at scale. From cluster setup to CI/CD integration, we handle the complexity. Get in touch.

Get in touch

# Kubernetes

Kubernetes (K8s) is an open source platform for automating deployment, scaling, and management of containerized applications. It turns a cluster of servers into a single pool of compute resources.

Category: Devops

Author: Atomic Glue Editorial Team

## Definition

## Why Kubernetes Exists

## Key Concepts

A **Cluster** is a set of machines (nodes) running Kubernetes. **Pods** are the smallest deployable unit: one or more containers that share networking and storage. **Deployments** manage stateless applications with desired replica counts and rolling updates. **Services** provide stable networking to a set of pods. **Ingress** exposes HTTP/HTTPS routes from outside the cluster. **ConfigMaps** and **Secrets** manage configuration and sensitive data separately from containers.

## When You Need Kubernetes

## Note

Managed Kubernetes (Amazon EKS, Google GKE, Azure AKS) is the recommended way to run K8s unless you have a dedicated infrastructure team. Self-managed clusters are significantly more work.

## In code

## Common questions
Q: Is Kubernetes the same as Docker?
A: No. Docker creates and runs containers. Kubernetes orchestrates containers across multiple machines. They work together: Docker packages the containers, Kubernetes manages them.
Q: Is Kubernetes overkill for a small project?
A: Almost certainly. For small projects, use Docker Compose or a platform like Vercel or Netlify. Kubernetes overhead only pays off at scale.

## Key takeaways

Kubernetes orchestrates containers across a cluster of machines, automating deployment, scaling, and healing.
It handles container placement, load balancing, rolling updates, and self-healing automatically.
Powerful but complex. Use managed K8s services (EKS, GKE, AKS) unless you have dedicated ops resources.
Overkill for small projects. Start with Docker Compose or PaaS platforms.

## Related entries

Last updated July 2026. Permalink: atomicglue.co/glossary/kubernetes