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Deployment with Service - Kubernetes Typing CST Test
Deployment with Service — Kubernetes Code
Demonstrates complete Kubernetes application deployment with configuration, secrets, services, and auto-scaling.
# Namespace
apiVersion: v1
kind: Namespace
metadata:
name: my-app
labels:
name: my-app
---
# ConfigMap for application configuration
apiVersion: v1
kind: ConfigMap
metadata:
name: app-config
namespace: my-app
data:
DATABASE_HOST: "postgres-service"
DATABASE_PORT: "5432"
REDIS_HOST: "redis-service"
REDIS_PORT: "6379"
---
# Secret for sensitive data
apiVersion: v1
kind: Secret
metadata:
name: app-secrets
namespace: my-app
type: Opaque
data:
DATABASE_PASSWORD: cGFzc3dvcmQxMjM= # base64 encoded
API_KEY: YWJjZGVmZ2hpams=
---
# Deployment
apiVersion: apps/v1
kind: Deployment
metadata:
name: my-app-deployment
namespace: my-app
labels:
app: my-app
spec:
replicas: 3
selector:
matchLabels:
app: my-app
template:
metadata:
labels:
app: my-app
spec:
containers:
- name: my-app
image: my-app:latest
ports:
- containerPort: 3000
env:
- name: DATABASE_HOST
valueFrom:
configMapKeyRef:
name: app-config
key: DATABASE_HOST
- name: DATABASE_PASSWORD
valueFrom:
secretKeyRef:
name: app-secrets
key: DATABASE_PASSWORD
resources:
requests:
memory: "256Mi"
cpu: "200m"
limits:
memory: "512Mi"
cpu: "500m"
livenessProbe:
httpGet:
path: /health
port: 3000
initialDelaySeconds: 30
periodSeconds: 10
readinessProbe:
httpGet:
path: /ready
port: 3000
initialDelaySeconds: 5
periodSeconds: 5
---
# Service
apiVersion: v1
kind: Service
metadata:
name: my-app-service
namespace: my-app
spec:
selector:
app: my-app
ports:
- protocol: TCP
port: 80
targetPort: 3000
type: LoadBalancer
---
# Horizontal Pod Autoscaler
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
name: my-app-hpa
namespace: my-app
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: my-app-deployment
minReplicas: 2
maxReplicas: 10
metrics:
- type: Resource
resource:
name: cpu
target:
type: Utilization
averageUtilization: 70
- type: Resource
resource:
name: memory
target:
type: Utilization
averageUtilization: 80Kubernetes Language Guide
Kubernetes is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications across clusters of machines.
Primary Use Cases
- ▸Orchestrating containerized applications
- ▸Automating deployment, scaling, and rollback
- ▸Managing microservices architectures
- ▸Providing service discovery and load balancing
- ▸Running hybrid or multi-cloud workloads
Notable Features
- ▸Automated container scheduling and placement
- ▸Self-healing via auto-restart, replication, and rescheduling
- ▸Horizontal scaling of pods based on metrics
- ▸Declarative configuration with YAML/JSON manifests
- ▸Extensible API for custom controllers and operators
Origin & Creator
Created by Google in 2014, based on internal Borg system, and now maintained by the Cloud Native Computing Foundation (CNCF).
Industrial Note
Kubernetes is widely used in enterprises and cloud-native environments to manage large-scale microservices, CI/CD pipelines, and automated infrastructure with high availability.
Quick Explain
- ▸Kubernetes provides automated container scheduling, scaling, and self-healing capabilities.
- ▸Supports declarative configuration via YAML or JSON manifests.
- ▸Manages container networking, storage, and service discovery automatically.
- ▸Extensible through custom controllers, operators, and APIs.
- ▸Facilitates hybrid and multi-cloud deployments for modern cloud-native applications.
Core Features
- ▸Pods - smallest deployable units in Kubernetes
- ▸Services - abstract network access to pods
- ▸Deployments - declarative updates and scaling
- ▸ConfigMaps and Secrets - configuration and sensitive data management
- ▸Namespaces - multi-tenancy and resource isolation
Learning Path
- ▸Learn Docker basics and container concepts
- ▸Understand Kubernetes architecture and objects
- ▸Deploy simple pods and services
- ▸Use Helm and Kustomize for templated deployments
- ▸Advance to multi-cluster, auto-scaling, and monitoring
Practical Examples
- ▸Deploy a web application with multiple replicas
- ▸Configure Ingress for HTTP routing
- ▸Set up Secrets for database credentials
- ▸Implement horizontal pod auto-scaling
- ▸Use Helm charts to package applications
Comparisons
- ▸Kubernetes vs Docker Swarm: more feature-rich, steeper learning curve
- ▸Kubernetes vs Nomad: Kubernetes offers extensive ecosystem and flexibility
- ▸Kubernetes vs OpenShift: OpenShift adds enterprise features and UI
- ▸Kubernetes vs Rancher: Rancher is management layer for Kubernetes clusters
- ▸Kubernetes vs ECS: ECS tightly integrated with AWS, Kubernetes is cloud-agnostic
Strengths
- ▸Highly scalable and resilient
- ▸Cloud-agnostic and portable
- ▸Strong ecosystem with tooling and extensions
- ▸Declarative and automated operations
- ▸Active community and enterprise support
Limitations
- ▸Steep learning curve for beginners
- ▸Operational complexity at scale
- ▸Debugging issues can be challenging
- ▸Resource-intensive compared to lightweight orchestrators
- ▸Requires good understanding of networking and storage concepts
When NOT to Use
- ▸Small projects without multiple containers
- ▸Single-node deployments where orchestration is unnecessary
- ▸Projects without expertise in DevOps or containerization
- ▸When lightweight container runtimes like Docker Compose suffice
- ▸Short-lived or experimental deployments without scaling needs
Cheat Sheet
- ▸kubectl get pods - list pods
- ▸kubectl describe pod <name> - inspect pod details
- ▸kubectl apply -f <manifest> - apply YAML configuration
- ▸kubectl logs <pod> - view pod logs
- ▸kubectl scale deployment <name> --replicas=3 - scale deployment
FAQ
- ▸Is Kubernetes open-source? -> Yes, under Apache 2.0 license.
- ▸Can it run on cloud and on-prem? -> Yes, fully hybrid and cloud-agnostic.
- ▸Does Kubernetes handle scaling automatically? -> Yes, via HPA/VPA.
- ▸Is it suitable for microservices? -> Yes, ideal for containerized microservices.
- ▸How to monitor Kubernetes? -> Use Prometheus, Grafana, and logging stacks.
30-Day Skill Plan
- ▸Week 1: Deploy simple pod and service on minikube
- ▸Week 2: Create deployments and manage replicas
- ▸Week 3: Configure ConfigMaps, Secrets, and volumes
- ▸Week 4: Implement Ingress and network policies
- ▸Week 5: Monitor and scale applications, integrate CI/CD
Final Summary
- ▸Kubernetes is a powerful container orchestration platform for modern cloud-native applications.
- ▸Automates deployment, scaling, networking, and storage management for containers.
- ▸Extensible, declarative, and highly resilient.
- ▸Supports hybrid and multi-cloud environments.
- ▸Backed by a strong community and ecosystem for enterprise-grade workloads.
Project Structure
- ▸manifests/ - Kubernetes YAML files
- ▸charts/ - Helm charts for templated deployments
- ▸src/ - application code
- ▸Dockerfile - container build configuration
- ▸k8s/ - scripts and utilities for cluster management
Monetization
- ▸Kubernetes is open-source (Apache 2.0)
- ▸Reduces operational costs via automation
- ▸Supports cloud-native enterprise workloads
- ▸Enables hybrid/multi-cloud deployments for business flexibility
- ▸Ecosystem tools enhance observability and productivity
Productivity Tips
- ▸Use Helm charts for repeatable deployments
- ▸Leverage Kustomize for environment customization
- ▸Apply RBAC and network policies early
- ▸Automate monitoring and alerts
- ▸Keep manifests version-controlled and modular
Basic Concepts
- ▸Pod - group of containers deployed together
- ▸Node - physical or virtual machine running pods
- ▸Service - abstraction for exposing pods
- ▸Deployment - manages pod replicas and updates
- ▸ConfigMap/Secret - external configuration and sensitive data
Official Docs
- ▸https://kubernetes.io/docs/
- ▸Kubernetes GitHub repository
- ▸CNCF community resources and tutorials