Day 8 – Kubernetes Basics: Orchestrating Containers in Production

Introduction

In modern DevOps ecosystems, Kubernetes (K8s) has become the de facto standard for container orchestration. While Docker allows developers to package applications into containers, Kubernetes ensures these containers run reliably and scale efficiently in production environments. At CuriosityTech.in, we guide aspiring DevOps engineers through both theory and hands-on implementation to master K8s.

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What is Kubernetes?

Kubernetes is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications. Originally developed by Google, K8s addresses the complexity of running applications at scale across clusters of machines.

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Key Benefits of Kubernetes

1. Scalability:– Automatically scale containers based on resource usage.
2. High Availability:– Self-healing features replace failed containers.
3. Load Balancing:– Distributes traffic evenly across containers.
4. Resource Optimization:– Efficiently utilizes hardware resources across nodes.
5. Extensibility:– Supports custom extensions, operators, and plugins.

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Core Concepts of Kubernetes

Component	Description
Pod	Smallest deployable unit in K8s; can contain one or more containers.
Node	Worker machine in the cluster, physical or virtual.
Cluster	Set of nodes managed by Kubernetes to run applications.
Deployment	Declarative object defining the desired state of Pods.
Service	Provides stable network access to Pods.
Namespace	Logical separation of resources within a cluster.
ConfigMap & Secret	Manage configuration and sensitive data.
Ingress	Manages external access, typically HTTP/HTTPS.

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Kubernetes Architecture Diagram

Description: The master node manages the cluster via the API server, scheduler, and controllers. Worker nodes run Pods containing containers, while Kubelet ensures the Pods run correctly.

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Kubernetes Workflow for Beginners

1. Write Deployment YAML:– Define replicas and container images.
2. Apply configuration:– kubectl apply -f <file>.yaml
3. Monitor Pods & Services:– kubectl get pods and kubectl get svc
4. Scale application:– kubectl scale deployment <name> --replicas=<number>
5. Update application:– Perform rolling updates without downtime.
6. Access logs & debug:– kubectl logs <pod> helps identify issues.

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Practical Example: Deploying a Simple Web Application

Deployment YAML Example:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: web-app
spec:
  replicas: 3
  selector:
    matchLabels:
      app: web
  template:
    metadata:
      labels:
        app: web
    spec:
      containers:
      - name: web
        image: nginx:latest
        ports:
        - containerPort: 80

Steps:

1. Apply deployment: kubectl apply -f web-deployment.yaml
2. Check pods: kubectl get pods
3. Expose service: kubectl expose deployment web-app --type=LoadBalancer --port=80
4. Retrieve external IP: kubectl get svc

At CuriosityTech.in, learners practice deploying applications on Minikube and managed cloud clusters such as AWS EKS, Azure AKS, and GCP GKE.

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Kubernetes vs Docker Swarm

Feature	Kubernetes	Docker Swarm
Complexity	High, steep learning curve	Low, simple for small projects
Scalability	Excellent for large clusters	Limited for large-scale clusters
Rolling Updates	Advanced, zero downtime	Supported, less flexible
Community	Very large ecosystem	Smaller community
Extensions	Helm, Operators, Controllers	Limited extension support

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Best Practices for Kubernetes Beginners

1. Use namespaces to isolate environments.
2. Leverage ConfigMaps and Secrets for configuration and sensitive data.
3. Adopt Helm to simplify complex deployments.
4. Implement monitoring using Prometheus and Grafana.
5. Understand resource requests and limits to prevent overconsumption.

Mastery comes through real-world deployments, multi-node clusters, and troubleshooting in production-like environments.

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Challenges & How to Overcome

Challenge	Solution
Steep Learning Curve	Start with Minikube or Kind for local practice.
Networking Complexity	Study ClusterIP, NodePort, LoadBalancer types.
Resource Management	Set CPU and memory limits for Pods.
Debugging Issues	Use kubectl describe, kubectl logs, and events.

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Infographic: Kubernetes Deployment Lifecycle

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Conclusion

Kubernetes is the backbone of scalable, production-grade containerized applications. Mastering its architecture, workflows, and best practices enables DevOps engineers to build highly available, fault-tolerant systems. Hands-on practice is crucial for true proficiency.

At CuriosityTech.in, we train learners to deploy multi-container apps, manage clusters, and integrate Kubernetes into CI/CD pipelines—ensuring they are industry-ready.