Imagine you have 50 microservices, each running multiple instances across a cluster of machines. Some services need to scale up during peak hours. Others need to restart when they crash. You need to deploy new versions without downtime, route traffic between services, and make sure a failure on one machine does not bring down your application.

Doing all this manually would be impossible. This is where Kubernetes comes in.

Kubernetes (often abbreviated as K8s) automates the deployment, scaling, and management of containerized applications across clusters. It handles the operational complexity that would otherwise require a team of operators working around the clock.

When a container crashes, Kubernetes restarts it. When traffic spikes, it can add more instances. When you deploy a new version, it rolls it out gradually to avoid downtime.

This chapter gives you the depth to discuss kubernetes confidently in interviews. We will cover cluster architecture, core abstractions, networking, storage, scaling, deployment strategies, and production considerations.

1. When to Choose Kubernetes