Deploying with Kubernetes: A Practical Guide

Getting a service running reliably on Kubernetes comes down to a handful of building blocks: a container image, a Deployment, and a Service to expose it. This walkthrough covers the essentials.

Before you start

You’ll need kubectl configured against a cluster (Minikube, kind, or a managed cluster all work fine for this walkthrough).

1. Build and tag the image

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docker build -t registry.example.com/api:1.4.0 .
docker push registry.example.com/api:1.4.0

2. Define the Deployment

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apiVersion: apps/v1
kind: Deployment
metadata:
  name: api
spec:
  replicas: 3
  selector:
    matchLabels:
      app: api
  template:
    metadata:
      labels:
        app: api
    spec:
      containers:
        - name: api
          image: registry.example.com/api:1.4.0
          ports:
            - containerPort: 8080
          readinessProbe:
            httpGet:
              path: /healthz
              port: 8080

3. Roll it out

bash

dev@k8s-master:~/api$

kubectl apply -f deployment.yaml deployment.apps/api created kubectl rollout status deployment/api deployment “api” successfully rolled out

Watch your readiness probes

A missing or too-strict readiness probe is the most common cause of a rollout that “succeeds” but serves traffic to pods that aren’t actually ready.

Architecture

Request flow

graph LR A[Client] --> B[Ingress] B --> C[Service] C --> D[Pod 1] C --> E[Pod 2] C --> F[Pod 3]

That’s the core loop: build, define, apply, verify. From here you’d typically add a HorizontalPodAutoscaler and wire this into CI so every merge to main triggers a new rollout automatically.