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Manthan Ankolekar
Manthan Ankolekar

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🚀 Deploying a Node.js Product API on Kubernetes with MongoDB

#webdev #node #aws #kubernetes

Modern apps need to scale effortlessly while staying resilient. Kubernetes (K8s) has become the go-to platform for orchestrating containerized apps, ensuring scalability, self-healing, and portability.

In this guide, we’ll build and deploy a Node.js Product API with MongoDB on Kubernetes. You’ll learn how to containerize the app, define Kubernetes manifests, and enable auto-scaling.

🧩 What We’re Building

  • A Node.js + Express REST API with CRUD for products
  • MongoDB database with Mongoose ODM
  • Dockerized application
  • Kubernetes resources: Deployment, Service, Ingress, Secrets
  • Horizontal Pod Autoscaler (HPA) for auto-scaling
  • Ingress Controller for external access

Here’s the flow:

Client → Ingress → Service → Pod(s) running Node.js API → MongoDB
                   ↑
                HPA scales pods dynamically
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📁 Project Structure 

nodejs-kubernates/
├── src/
│   ├── config/db.js          # MongoDB connection
│   ├── controllers/          # Business logic
│   ├── models/product.model.js
│   ├── routes/product.routes.js
│   ├── middlewares/          # Error handling, validation
│   └── server.js             # Express entry point
├── k8s/
│   ├── deployment.yaml       # App Deployment
│   ├── service.yaml          # ClusterIP Service
│   ├── ingress.yaml          # Ingress (exposes API)
│   ├── secret.yaml           # MongoDB credentials
│   └── hpa.yaml              # Auto-scaling config
├── Dockerfile
├── docker-compose.yml        # Local dev
└── package.json
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📝 Step 1 — Build the Node.js Product API

The Product schema:

const productSchema = new mongoose.Schema({
  name: { type: String, required: true, trim: true },
  description: { type: String, default: '' },
  price: { type: Number, required: true, min: 0 },
  inStock: { type: Boolean, default: true }
}, { timestamps: true });
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CRUD endpoints are exposed at /api/products.
Example request:

curl -X POST http://localhost:5000/api/products \
  -H "Content-Type: application/json" \
  -d '{"name":"Laptop","price":999.99,"inStock":true}'
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📦 Step 2 — Containerize with Docker

Dockerfile:

FROM node:18-alpine
WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production
COPY . .
CMD ["node", "src/server.js"]
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Build and run locally:

docker build -t nodejs-kubernates .
docker run -p 5000:5000 \
  -e MONGO_URI=mongodb://host.docker.internal:27017/product-api \
  nodejs-kubernates
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☸️ Step 3 — Kubernetes Manifests

Deployment (deployment.yaml) 

apiVersion: apps/v1
kind: Deployment
metadata:
  name: product-api
spec:
  replicas: 2
  selector:
    matchLabels:
      app: product-api
  template:
    metadata:
      labels:
        app: product-api
    spec:
      containers:
        - name: product-api
          image: <REGISTRY>/nodejs-kubernates:latest
          ports:
            - containerPort: 5000
          env:
            - name: MONGO_URI
              valueFrom:
                secretKeyRef:
                  name: app-secrets
                  key: MONGO_URI
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Service (service.yaml) 

apiVersion: v1
kind: Service
metadata:
  name: product-api-svc
spec:
  selector:
    app: product-api
  ports:
    - port: 80
      targetPort: 5000
  type: ClusterIP
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Ingress (ingress.yaml) 

apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: product-api-ingress
  annotations:
    kubernetes.io/ingress.class: alb
spec:
  rules:
    - http:
        paths:
          - path: /
            pathType: Prefix
            backend:
              service:
                name: product-api-svc
                port:
                  number: 80
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Secrets (secret.yaml) 

apiVersion: v1
kind: Secret
metadata:
  name: app-secrets
type: Opaque
data:
  MONGO_URI: <base64-encoded-uri>
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Encode your Mongo URI:

echo -n "mongodb://user:pass@host:27017/product-api" | base64
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HPA (hpa.yaml) 

apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: product-api-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: product-api
  minReplicas: 2
  maxReplicas: 10
  metrics:
    - type: Resource
      resource:
        name: cpu
        target:
          type: Utilization
          averageUtilization: 70
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🚀 Step 4 — Deploy to Kubernetes

  1. Push your Docker image to a registry (DockerHub, AWS ECR, GCP Artifact Registry).
  2. Apply manifests: 
kubectl apply -f k8s/
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  1. Check status: 
kubectl get pods
kubectl get svc
kubectl get ingress
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  1. Access the API: 
curl http://<INGRESS-HOST>/api/products
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📊 Step 5 — Scaling & Monitoring

  • HPA automatically scales pods between 2–10 based on CPU/memory usage.
  • Liveness & Readiness probes ensure only healthy pods receive traffic.
  • Logging & Monitoring: Add Prometheus + Grafana, or pipe logs to ELK/CloudWatch.

🔒 Production Considerations

  • Use managed MongoDB (Atlas, DocumentDB).
  • Enable TLS/HTTPS for ingress (cert-manager + Let’s Encrypt).
  • Store secrets in Kubernetes Secrets or external vaults.
  • Define resource requests & limits for predictable scaling.
  • Add a CI/CD pipeline to build, push, and deploy automatically.

🎯 Conclusion

You’ve just deployed a Node.js Product API on Kubernetes with:
✅ Dockerized app
✅ Kubernetes Deployment, Service & Ingress
✅ Secrets for sensitive data
✅ Auto-scaling with HPA

This setup provides a strong foundation for microservices in production.

🔗 GitHub Repository: manthanank/nodejs-kubernates
🧑‍💻 Author: Manthan Ankolekar

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