Kubernetes Architecture Simplified: Control Plane & Worker Nodes

🚀 Understanding Kubernetes Architecture (Made Simple) Kubernetes looks complex at first—but once you break it down, it’s actually very logical. At a high level, Kubernetes is divided into 2 main parts: 🔹 Control Plane (Brain) 🔹 Worker Nodes (Execution) 👉 Control Plane Components: API Server → Entry point for all operations Scheduler → Decides where pods run Controller Manager → Maintains desired state ETCD → Stores cluster data 👉 Worker Node Components: Kubelet → Talks to control plane Kube Proxy → Handles networking Container Runtime → Runs containers 📌 Flow: You → API Server → Scheduler → Node → Pod → Container runs The beauty of Kubernetes: ✔ Self-healing ✔ Auto-scaling ✔ Load balancing ✔ High availability 💡 Key Insight: Kubernetes is not about running containers — it’s about managing them efficiently at scale. #Kubernetes #DevOps #Cloud #Containers #Learning

🚀 Day 2 of Learning Kubernetes Today I deep-dived into Kubernetes Architecture and how it works internally. 📌 What I learned: • Overall Kubernetes architecture (Control Plane + Worker Nodes) • Components of Control Plane (API Server, Scheduler, etcd, Controller Manager) • Components inside Worker Nodes (kubelet, kube-proxy, Pods) • How communication happens between components. 🧠 Key Concept: Kubernetes follows a master-worker architecture where the Control Plane manages the cluster and Worker Nodes run the actual applications (pods). 🏗️ Architecture Breakdown: 🔹 Control Plane (Managed by AWS in EKS): • API Server – Entry point for all commands (kubectl) • Scheduler – Assigns pods to nodes • etcd – Stores cluster state • Controller Manager – Maintains desired state. 🔹 Worker Nodes (EC2 instances): • kubelet – Communicates with control plane • kube-proxy – Handles networking • Pods – Smallest deployable unit (containers run here). 🔹 Networking: • Uses VPC and AWS CNI • Each pod gets its own IP • Enables pod-to-pod communication. 🔹 Security & Access: • IAM roles and Security Groups • Secure communication via API Server (HTTPS). ⚙️ What I did: • Explored EKS architecture components • Observed node and pod behavior using kubectl • Understood how control plane interacts with worker nodes 🚀 Takeaway: Understanding architecture has given me a clarity on how Kubernetes manages scaling, self-healing, and deployment automatically. #Kubernetes #AWS #EKS #DevOps #Cloud #LearningJourney #100DaysOfCode

🐳 Understanding the Core Components of Docker Docker is not just a tool — it has become a fundamental part of modern DevOps and application deployment. Today, I revisited the core components of Docker and explored how each plays a crucial role in containerization: 🔹 Docker Client – The interface used to interact with Docker 🔹 Docker Daemon – The backend service that manages containers and images 🔹 Docker Image – A blueprint used to create containers 🔹 Docker Container – A lightweight, isolated environment to run applications 🔹 Dockerfile – A script that defines how an image is built 🔹 Docker Network – Enables communication between containers 🔹 Docker Volume – Provides persistent data storage 🔹 Docker Registry – Stores and distributes Docker images 🔹 Docker Host – The machine where Docker runs 🔹 Plugins – Extend Docker’s capabilities Understanding these fundamentals is essential for anyone stepping into DevOps, Cloud Computing, CI/CD, or Kubernetes. #Docker #DevOps #Containers #CloudComputing #AWS #Linux #Kubernetes

At some point, every team working with containers faces the same question build the platform yourself, or adopt one that’s already integrated. Read how Kubernetes and OpenShift approach that trade-off in practice. https://lnkd.in/d4-xvEei #CloudOptimo #K8s #OpenShift

🚀 Just shipped a production-style Kubernetes infrastructure on AWS — fully automated with Terraform and GitLab CI/CD! Here's what I built: ✅ Amazon EKS cluster provisioned with Terraform ✅ AWS VPC with public & private subnets across multiple AZs ✅ Remote Terraform state with S3 + DynamoDB locking ✅ GitLab CI/CD pipeline with validate → plan → apply → destroy stages ✅ Manual approval gates for apply and destroy ✅ GitHub + GitLab mirror for automatic sync The goal wasn't just to spin up a cluster — it was to build infrastructure the way it's done in production: repeatable, automated, and safe. 🔗 GitHub: https://lnkd.in/e7YZkCXp #Kubernetes #Terraform #AWS #EKS #DevOps #IaC #GitLabCI #CloudEngineering #PlatformEngineering

🚀 Deployed a Full Stack Application on AWS EKS (Kubernetes) with Domain Routing & Ingress Excited to share my recent hands-on project where I successfully deployed a frontend and backend application on AWS using Kubernetes. ⸻ 🔧 What I implemented: • Containerized applications using Docker • Pushed images to Amazon ECR • Created and managed Kubernetes cluster using Amazon EKS • Deployed frontend & backend using Kubernetes Deployments & Services • Configured Ingress using AWS Load Balancer Controller • Implemented domain-based routing: • portal.domain.com → Frontend • api.domain.com → Backend • Configured DNS using Route 53 ⸻ 🌐 Architecture Highlights: • Single EKS cluster hosting multiple services • ALB Ingress for traffic routing • Internal communication via ClusterIP services • Secure and scalable microservices setup ⸻ ⚙️ Challenges & Learnings: • Fixed IAM OIDC provider issue for ALB controller • Resolved image pull issues with ECR permissions • Debugged API communication (CORS & routing) • Understood Kubernetes networking (Service, targetPort, containerPort) ⸻ 💡 What’s Next: • CI/CD pipeline using Jenkins / GitLab CI/CD • Monitoring with Prometheus & Grafana • Infrastructure as Code using Terraform ⸻ 🔥 This project gave me real-world exposure to production-level DevOps workflows on Kubernetes. ⸻ #DevOps #AWS #Kubernetes #EKS #Docker #CloudComputing #CI_CD #Learning #Projects #CloudEngineer #Infrastructure #Tech

🚀 Exploring Kubernetes Architecture (K8s) – The Backbone of Modern DevOps Understanding Kubernetes at a deeper level is essential for building scalable and production-ready systems in today’s cloud-driven world 💡 🔹 Control Plane – Orchestrates and manages the entire cluster 🔹 Worker Nodes – Execute workloads through Pods 🔹 Core Components – API Server, Scheduler, Controller Manager & etcd ensure seamless cluster operations 📌 This architecture highlights how modern applications achieve high availability, scalability, and fault tolerance in real-world environments. Currently strengthening my DevOps skillset by working with Kubernetes, AWS, Docker, and CI/CD pipelines 🚀 📈 Focused on continuous learning and building real-world expertise in cloud and DevOps. #Kubernetes #DevOps #AWS #Docker #Jenkins #CloudComputing #K8s #Learning #CareerGrowth

Today Morning I faced an Interview at IBM for AWS DevOps Engineer 1. Self introduction 2. explain Kubernetes architecture 3. have you worked on auto-scaling in Kubernetes? 4. difference between HPA and VPA 5. explain what happens when a POD crashes? 6. How we explore the applications which are running on Kubernetes clusters. 7. Explain Terraform modules which you are writing for your project? 8. write a sample Terraform module to launch an EC2 instance? 9. Instance types are you aware of and which instance type have you used? 10. Explain and write stages of pipeline in your project? 11. Write a simple Dockerfile and explain? 12. If the Docker animate size is huge, how do you reduce it? 13. difference between ALB and NLB #devops #awsdevops #clouddevops #terraform #jenkins #kubernetes #docker #aws #devopsengineer

👨💻 Learn how to deploy applications, manage workloads, implement autoscaling, and monitor performance using Minikube. A practical, end-to-end guide to running Kubernetes locally with real-world concepts and hands-on execution Read here : https://lnkd.in/dWKyDKF3 #Kubernetes #Containers #Docker #K8s #Automation #Scalability #CloudOptimo

Kubernetes is powerful… but only if you know how to operate it. Most people learn Kubernetes like theory 📚 But in real-world systems? 👉 It’s all about commands, control, and clarity under pressure ⸻ 💡 Kubernetes is not just orchestration… it’s layered engineering 📖 As outlined in this cheat sheet Kubernetes operates across multiple layers: 👉 Infrastructure 👉 Automation 👉 Orchestration 👉 CI/CD pipelines All working together as a single system ⸻ 🧠 What makes Kubernetes different (and powerful): 🔹 Declarative → You define the desired state 🔹 Immutable → Changes create new versions, not patch old ones 🔹 Abstracted → Infrastructure complexity is hidden (From the executive summary section) ⸻ ⚙️ Real operational components (page 4 breakdown): 👉 Master Node • API Server → Entry point • Scheduler → Decides placement • Controller Manager → Maintains state 👉 Worker Node • Kubelet → Keeps pods running • Kube-proxy → Handles networking (Clearly shown in the architecture diagram on page 4) ⸻ 📦 Core Kubernetes building blocks: From the constructs section (page 7) 🔹 Pods → Smallest deployable unit 🔹 Deployments → Manage lifecycle 🔹 Services → Stable networking layer 🔹 ReplicaSets → Maintain availability 🔹 Ingress → External traffic routing 👉 These are not just objects… They are control mechanisms ⸻ 🔥 Where theory ends and real engineering begins: 👉 The terminal 📌 From the commands section (pages 8–10): ✔ kubectl get pods → See what’s running ✔ kubectl apply -f → Deploy changes ✔ kubectl scale → Handle load ✔ kubectl drain → Maintain nodes ✔ kubectl autoscale → Dynamic scaling ⸻ ⚡ Real-world mindset: Before: ❌ “I know Kubernetes concepts” After: ✅ “I can operate a cluster under load, failure, and scale” ⸻ 🌐 And here’s what most people miss: Kubernetes alone is not enough From the ecosystem section (page 6): 👉 Monitoring (Prometheus) 👉 Logging (ELK/Fluentd) 👉 CI/CD pipelines 👉 Ingress controllers 👉 Container registries 👉 Kubernetes is the core… But the ecosystem is what makes it production-ready ⸻ 💡 Final thought: Don’t just learn Kubernetes concepts… Learn how to run Kubernetes systems Because that’s where real value is built ⸻ #Kubernetes #DevOps #Cloud #K8s #Docker #Containers #CloudNative #SRE #Automation #Infrastructure #AWS #Azure #GCP #CI_CD #Deployment #Scalability #SystemDesign #Engineering #Tech #Programming #Developers #IT #CloudComputing #OpenSource #Networking #Security #Observability #PlatformEngineering #Kubectl #Microservices