#Kubernetes
136 posts
K8s Basics #4: Deployment and ReplicaSet — Declarative Deploys and Rolling Updates
A follow-up to the closing line of [#3](/en/posts/k8s-basics-3) — Pods are mortal, they just disappear when they die. This post writes a controller manifest for the first time. We pin down the three layers Deployment / ReplicaSet / Pod, watch auto-recovery when one Pod is deleted under replicas: 3, see how a one-character image-tag change drives a rolling update, and roll back a bad version with one command.
K8s Basics #3: kubectl and Your First Pod
Time to put your first workload onto the cluster from [#2](/en/posts/k8s-basics-2). We pin the kubectl command pattern in one table, bring up a first Pod imperatively with kubectl run, then rewrite the same shape as a YAML manifest. We inspect the Pod with describe / logs / exec, and end on the question — why one Pod is not enough, which is exactly why the next post needs Deployment.
K8s Basics #2: Local Environments — minikube / kind / Docker Desktop k8s
Time to actually meet the control plane / worker picture from [#1](/en/posts/k8s-basics-1). Compare the three ways to run K8s on a laptop (minikube / kind / Docker Desktop k8s), install kubectl, and bring up your first cluster with kind — through to inspecting the nodes and system pods.
K8s Basics #1: What Is Kubernetes — Why Do We Need a Container Orchestrator?
You can run a single container with Docker. But what if you need 100 — and they need to restart on failure, scale with traffic, and survive a node going down? This first post in the series covers the limits of single-container tools, the problem container orchestrators solve, and the big picture of a Kubernetes cluster.