Kubernetes (K8s) is a container orchestration platform that automates deploying, scaling, and managing containerized applications across clusters of machines. Originally developed by Google based on their internal Borg system, it handles the operational complexity of running containers at scale: health checking, load balancing, rolling updates, and automatic recovery from failures.
How It Works
Kubernetes organizes containers into Pods, the smallest deployable units, typically containing one application container. Deployments manage Pod replicas, ensuring the desired number of instances are always running. Services provide stable networking endpoints that route traffic to healthy Pods. Ingress controllers manage external HTTP access with routing rules and TLS termination.
A cluster consists of a control plane (managing state and scheduling) and worker nodes (running Pods). You declare desired state in YAML manifests: "I want 3 replicas of my API server, each with 512MB memory, exposed on port 8080." Kubernetes continuously reconciles actual state with desired state, restarting crashed containers and rescheduling Pods from failed nodes.
Managed Kubernetes Options
Running Kubernetes yourself is complex. Managed options reduce operational burden significantly:
- EKS (AWS): Managed Kubernetes on AWS with deep integration into AWS services
- GKE (Google Cloud): The most mature managed offering, from Kubernetes' original creators
- AKS (Azure): Microsoft's managed Kubernetes service
These services handle control plane management, upgrades, and security patches while you focus on your applications.
When NOT to Use Kubernetes
Kubernetes has significant operational complexity. It requires dedicated expertise, careful RBAC configuration, and ongoing maintenance. For teams running fewer than five services, managed platforms (Vercel, Railway, Fly.io) provide similar benefits with dramatically less overhead.
Consider alternatives when:
- Your team is small (under 5 engineers)
- You are running fewer than 5 services
- Your traffic patterns are predictable
- You do not have Kubernetes expertise in-house
Kubernetes makes sense when you have the team size and service count to justify the investment.
Why It Matters
Running containers on a single server is simple. Running them across dozens of servers with zero downtime, automatic scaling, and graceful updates is not. Kubernetes solves this orchestration problem. It handles rolling deployments that gradually replace old Pods with new ones, horizontal auto-scaling based on CPU or custom metrics, and self-healing when containers crash.
For organizations running many services, Kubernetes provides a consistent deployment model regardless of the underlying cloud provider.
In Practice
A SaaS company runs 15 microservices on Kubernetes. During a traffic spike, the Horizontal Pod Autoscaler detects increased CPU usage on the API service and scales from 3 to 12 replicas in under a minute. When traffic subsides, it scales back down. A faulty deployment is automatically rolled back when health checks fail.
Learn More
- AWS Cloud Development – EKS and container services
- Enterprise Development – Large-scale infrastructure
- Node.js Development – Containerized Node applications
- SaaS Development – Multi-service SaaS architecture